WORKING
P A P E R
Analysis of Case-Mix
Strategies and
Recommendations for
Medicare Fee-for-Service
CAHPS
Case-Mix Adjustment Report: 2004
MARC N. ELLIOTT, KATRIN HAMBARSOOMIANS,
AND CAROL A. EDWARDS
WR-332-CMS
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December 2005
Prepared for Edward Sekscenski
Centers for Medicare & Medicaid Services
7500 Security Boulevard
Mail Stop S1-15-03
Baltimore, MD 21244
August 2005
Analysis of Case-Mix Strategies and
Recommendations for Medicare
Fee-for-Service CAHPS
Case-mix Adjustment Report: 2004
Prepared for
Edward S. Sekscenski
Centers for Medicare & Medicaid Services
7500 Security Boulevard
Mail Stop S1-15-03
Baltimore, MD 21244
Prepared by
RAND Corporation
Under subcontract to
Center for Health Systems Research and Analysis
University of Wisconsin-Madison
and RTI International
Contract No. 500-95-0061
RTI Project Number 07903.200
RAND Project Number HE406
ANALYSIS OF CASE-MIX STRATEGIES AND RECOMMENDATIONS FOR MEDICARE
FEE-FOR-SERVICE CAHPS
CASE-MIX REPORT: 2004
RAND Task Leader: Marc N. Elliott
RAND MFFS Team: Katrin Hambarsoomians and Carol Edwards
Federal Project Officer: Edward S. Sekscenski
RAND Corporation
Contract No. 500-95-0061
RTI Project Number 07903.200
RAND Project Number HE406
August 2005
The statements contained in this report are solely those of the authors and do not necessarily
reflect the views or policies of the Centers for Medicare & Medicaid Services. The awardee
assumes responsibility for the accuracy and completeness of the information contained in this
report.
ACKNOWLEDGEMENTS
The authors wish to thank the Ted Sekscenski, the RTI MFFS team and the Harvard
MMA team for their collegial and expert contributions to our mutual work. We also wish to
thank Megan Beckett for comments on the report and Colleen Carey for assistance in the
preparation of the manuscript.
ii
CONTENTS
EXECUTIVE SUMMARY ............................................................................................................ 1
INTRODUCTION .......................................................................................................................... 5
SUMMARY OF DATA AND VARIABLES................................................................................. 7
Data.............................................................................................................................................. 7
Variables...................................................................................................................................... 7
GENERAL ANALYTIC APPROACH ........................................................................................ 11
Assumptions of CMA................................................................................................................ 11
Desirable Properties of CMA Models ....................................................................................... 12
Imputation of Missing Values for CMA Variables ................................................................... 13
SUMMARY OF MFFS PILOT TEST CASE-MIX ADJUSTMENT REPORT.......................... 15
OVERVIEW OF 2004 CASE-MIX REPORT ............................................................................. 17
OVERVIEW OF 2000-2004 CASE-MIX FINDINGS AND TRENDS....................................... 18
DISTINCTIONS BETWEEN MFFS-VS.-MA CMA AND WITHIN-MFFS CMA ................... 21
TESTING MODEL ASSUMPTIONS FOR CMA ....................................................................... 22
Linearity..................................................................................................................................... 22
Homogeneity for MFFS-vs.-MA CMA..................................................................................... 24
Homogeneity for Within–MFFS CMA ..................................................................................... 29
SELECTING VARIABLES FOR THE CASE-MIX MODEL .................................................... 33
Models Compared...................................................................................................................... 33
Explanatory Power of Case-Mix Adjusters ............................................................................... 34
Precision of Case-Mix Adjuster Estimates................................................................................ 38
Robustness to Dichotomization of Outcomes in Reporting ...................................................... 39
Stability of MFFS CMA Coefficients ....................................................................................... 40
Recommendations for Case-Mix Adjustments.......................................................................... 49
IMPACT OF CASE-MIX ADJUSTMENT OF GEO UNITS WITHIN MFFS, USING
CONTINUOUS SCORING .......................................................................................................... 51
IMPACT OF CASE-MIX ADJUSTMENT OF STATES WITHIN MFFS, USING
PERCENTAGE SCORING .......................................................................................................... 52
IMPACT OF CASE-MIX ADJUSTMENT AND COMPARISON WEIGHTS ON NATIONAL
MFFS VS. MA COMPARISON .................................................................................................. 55
IMPACT OF CASE-MIX ADJUSTMENT ON STATE-LEVEL MFFS VS. MA
COMPARISONS, USING PERCENTAGE SCORING .............................................................. 59
SUMMARY OF IMPACT OF CASE-MIX ADJUSTMENT ...................................................... 63
APPENDIX A: CASE-MIX ADJUSTMENT COEFFICIENTS ................................................. 65
APPENDIX B: CONSTRUCTION OF GEOGRAPHIC EQUIVALENCE WEIGHTS (GEWS)
..................................................................................................................................................... 161
APPENDIX C: NOTES ON CASE-MIX ADJUSTMENT OF THOSE UNDER AGE 65 (2000
Data)............................................................................................................................................ 165
APPENDIX D: EXPLORATORY ANALYSIS OF CURRENT LIFE SATISFACTION ITEM
ON 2002 AND 2003 MFFS SURVEYS..................................................................................... 176
APPENDIX E: SUPPLEMENTARY TABLES FROM EARLIER REPORTING YEARS ..... 180
APPENDIX F: ISSUES REGARDING CASE-MIX ADJUSTMENT FOR MODE (2002
DATA) ........................................................................................................................................ 187
REFERENCES ........................................................................................................................... 188
iii
TABLES
Table ES-1: Description of Independent Variables Used in MFFS Case-Mix Adjustment, 2004
(Year 5) .................................................................................................................................... 1
Table 1: CAHPS ratings and composites........................................................................................ 7
Table 2: Description of independent variables used in MFFS case-mix adjustment...................... 8
Table 3: States comprising CMS Regions ...................................................................................... 9
Table 4: F-Statistics for the Null Hypothesis of Linearity of Ordinal Case-Mix Adjusters, Global
Ratings, 2000 – 2004.............................................................................................................. 23
Table 5.1: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2004) ..................................................................................................................................... 24
Table 5.2: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(Years 2000-2004).................................................................................................................. 26
Table 6. P-values for partial F-tests of heterogeneity of Within-FFS Case-Mix Effects by CMS
by Region, Years 2000-2004.................................................................................................. 30
Table 7: Coefficients of Linear Interactions of Case-Mix Adjusters with CMS Regions,
Excluding Dually Eligibles, Years 2000 – 2004. ................................................................... 32
Table 8a: Explanatory Power of Group 1 (Base Model) Case-Mix Adjusters, Geo Unit
Reporting Entities, Years 2002 – 2004 .................................................................................. 35
Table 8b: Explanatory Power of Group 2 (Prospective) Case-Mix Adjusters, Geo Unit Reporting
Entities, Years 2002 – 2004 ................................................................................................... 37
Table 9: Characteristics of Appendix Tables Listing Model Coefficients .................................. 38
Table 10: Comparison of 2000- 2004 MFFS CMA Coefficients for Base Model plus MHP, MA
and MFFS Common States, No Dual Eligibles, Geo Unit Dummies Included in the Models
................................................................................................................................................ 42
Table 11: 2000-2004 Impact of Within-MFFS CMA, Geo Unit Reporting Entities, Base Model +
MHP ....................................................................................................................................... 51
Table 12: 2001-2004 Impact of Within-MFFS CMA, State Reporting Entities, Base Model +
MHP, Percentage Scoring ...................................................................................................... 53
Table 13: 2001-2004 National Estimates of MFFS-MA difference, Base Model + MHP,
Percentage Scoring, Unadjusted, Comparison Weighted, and Comparison Weighted + CaseMix Adjusted.......................................................................................................................... 57
Table 14: 2001-2004 Impact of CMA on State-Level MFFS-MA Difference, Base Model +
MHP, Percentage Scoring ...................................................................................................... 60
Table A1a: 2000 Case-Mix Coefficients, Base Model, No Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities .............................................................................. 65
Table A1a_d: 2000 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities ............. 71
Table A1b: 2001 MFFS Case-Mix Coefficients, Base Model, No Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities .............................................................................. 72
Table A1b_d: 2001 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities ............. 77
Table A1c: 2002 Case-Mix Coefficients, Base Model, No Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities .............................................................................. 78
Table A1c_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model,
No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities.......................... 83
iv
Table A2a: 2000 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................... 84
Table A2b: 2001 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................... 90
Table A2c: 2002 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................... 96
Table A2d: 2003 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................. 103
Table A2e: Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities ............................................................................ 110
Table A2e_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model
Plus MHP, With Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities .. 116
Table A3b: 2001 Case-Mix Coefficients, Base Model Plus MHP, No Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................. 117
Table A3c: 2002 Case-Mix Coefficients, Base Model Plus MHP, No Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................. 123
Table A3d: 2003 Case-Mix Coefficients, Base Model Plus MHP, No Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities............................................................. 129
Table A3b_d: 2001 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
.............................................................................................................................................. 135
Table A3c_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model
Plus MHP, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities ..... 136
Table A3d_d: 2003 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
.............................................................................................................................................. 137
Table A4c: 2002 Case-Mix Coefficients, Base Model Plus MHP, Plus Life Satisfaction, No Dual
Eligibles, No Regional Interactions, Geo Unit Reporting Entities ...................................... 138
Table A4d: 2003 Case-Mix Coefficients, Base Model Plus MHP, Plus Life Satisfaction, No Dual
Eligibles, No Regional Interactions, Geo Unit Reporting Entities ...................................... 145
Table A4c_d: 2002 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, Plus Life Satisfaction, No Dual Eligibles, No Regional Interactions, Geo
Unit Reporting Entities......................................................................................................... 151
Table A4d_d: 2003 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, Plus Life Satisfaction, No Dual Eligibles, No Regional Interactions, Geo
Unit Reporting Entities......................................................................................................... 152
Table A5e: Case-Mix Coefficients, Base Model Plus MHP, Plus Life Satisfaction, With Dual
Eligibles, No Regional Interactions, Geo Unit Reporting Entities ...................................... 153
Table A5e_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model
Plus MHP, Plus Life Satisfaction, With Dual Eligibles, No Regional Interactions, Geo Unit
Reporting Entities................................................................................................................. 160
Table C1a: Differential Response of the Disabled Population (age < 65) on the GHP Item, CMA
analysis, 2000, 43 States with MA, Excluding Dual Eligibles ............................................ 168
Table Clb: Differential Response of the Disabled Population (age < 65) on the Health Survey
Item, CMA analysis with Additional Age Categories, Year 2000, 43 States with MA, No
Dual Eligibles....................................................................................................................... 170
v
Table C2a: 2000 Comparison of Global Ratings by those under 65 to those 70-74 and in Good
Health ................................................................................................................................... 171
Table C2b. 2000 Comparison of Global Ratings by three age categories under age 65 to those
70-74 and in Good Health (model includes GHP by ‘Age<65’ interaction) ....................... 172
Table D1. Multiple Regressions Examining the Impact of Current Life Satisfaction on Subgroup
Comparisons......................................................................................................................... 178
Table E1a: Comparison of Magnitude of CMA Coefficients, FFS vs. MA (2000).................... 180
Table E1b: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2001) ................................................................................................................................... 181
Table E1c: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2002) ................................................................................................................................... 182
Table E1d: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2003) ................................................................................................................................... 183
Table E2a: Explanatory Power of Group 1 (Base Model) Case-Mix Adjusters, Geo Unit
Reporting Entities, Years 2000 – 2001 ................................................................................ 184
Table E2b: Explanatory Power of Group 2 (Prospective) Case-Mix Adjusters, Geo Unit
Reporting Entities, Excluding Dually Eligible Beneficiaries, Years 2000 – 2001 .............. 185
Table E3: Comparison of 2000- 2002 MFFS CMA Coefficients for the 2000-2001 Base Model
(no MHP), 43/44 States Common with MA, Excluding Dually Eligible Beneficiaries, Geo
Unit Dummies ...................................................................................................................... 186
FIGURES
Figure 1. Parameter estimates from Table 10 plotted against age, by global rating, years 20002004........................................................................................................................................ 45
Figure 2. Parameter estimates from Table 10 plotted against education, by global rating, years
2000-2004............................................................................................................................... 46
Figure 3. Parameter estimates from Table 10 plotted against GHP, by global rating, years 20002004........................................................................................................................................ 47
Figure 4. Parameter estimates from Table 10 plotted against MHP, by global rating, years 20002004........................................................................................................................................ 48
Figure C1: 2000 Comparison of Global Ratings by those under 65 to those 70-74 and in Good
Health ................................................................................................................................... 173
Figure C2: 2000 illustration of linear pattern in age among beneficiaries under 65, 43 States with
MA, no dual eligibles ........................................................................................................... 175
vi
EXECUTIVE SUMMARY
For readers familiar with the 2000-2002 (Years 1-3) Case-Mix Reports, we will briefly
describe how this report differs from the previous year’s report. First, this report seeks to
evaluate the stability of many of the findings and resultant decisions from the 2000-2002 CaseMix Reports, including the choice of case-mix adjusters, their parameterization, and their impact.
Second, we have reformatted the presentation of information in a way that favors comparative
tables across years were possible and which relegates older data to the Appendix when this is not
possible, with the hopes of producing a more concise document.
The Medicare Fee-for-Service (MFFS) Consumer Assessment of Health Plans (CAHPS)
project is centered around two types of comparisons: beneficiary comparisons of MFFS and
Medicare Advantage (MA, formerly Medicare Managed Care) within local areas and
administrative comparisons of MFFS across local areas. Case-mix adjustment (CMA) is a
central element in these comparisons. CMA attempts to remove from ratings and reports of care
response patterns that are systematically associated with such patient-level characteristics as
demographics, socio-economic status, and general health status, which may vary considerably
across reporting units. These systematic patterns of association may reflect “response bias,”
response patterns that do not correspond to actual differences in quality of care. In any event,
these are patient characteristics that are generally agreed to be beyond the control of providers or
plans once they have been selected by beneficiaries. The goal of CMA can therefore be thought
of as follows: to estimate the ratings and reports that a plan or collection of FFS providers would
have received if all providers and plans treated the same standardized population of patients
(Medicare beneficiaries). This adjustment should make attributions of ratings and reports to FFS
providers and MA plans more appropriate, supporting better decision-making by beneficiaries
and quality improvement by PROs and HCFA.
The two goals of MFFS CMA (within-MFFS comparison and MFFS-vs.-MA
comparison) suggest two different, but similar, CMA models. Table ES-1 describes the
independent variables recommended for case-mix adjustment. This set of variables is the same
as that used in the previous year.
Table ES-1: Description of Independent Variables Used in MFFS Case-Mix Adjustment, 2004
(Year 5)
Name (Dummies)
Description
Response Options
AGE (AGE44, AGE4564,
Age
<44, 45-64, 65-69, 70-74, 75AGE6569, AGE7579,
79, 80-85, >85
AGE8085, AGE85)
1
EDUC
(LESS8GRD, SOMEHIGH,
SOMECOLL, COLLGRAD,
COLLMORE)
Education
GHP
General health perception
(EXCEL, VERYGOOD, FAIR,
POOR)
MHP
Mental health perception
(MHEXCEL, MHGOOD,
MHFAIR, MHPOOR)
(PROXY, ANSPROXY)
Proxy respondent status
DUALELIG1
<8th grade, some high school,
high school graduate or GED,
some college (but less than 4
yr. Degree), 4 year college
graduate, >college graduate
(some graduate school beyond
the 4 year degree)
Excellent, very good, good,
fair, poor
Excellent, very good, good,
fair, poor
No assistance on survey,
someone helped but did not
answer for you, someone
answered for you
Yes, no
Dual-eligibility indicator
(eligible for Medicaid
program)
The present study found that the case-mix adjusters employed in 2001-2003 MFFS-vs.MA CMA (age, education, self-rated health status, self-rated mental health status and proxy
respondent status2) constitute an effective case-mix model for both comparison purposes. Selfrated health, self-rated mental health, and education were the three most important CMA
variables. An indicator of dual-eligibility, long used in the within-MFFS model, is a useful
addition to the MFFS-vs.-MA model, given the new inclusion of the dually eligible in these
comparisons. These findings are consistent with CMA results for 2000-2003.
Within-MFFS CMA employs the above independent variables plus dummies
corresponding to the geographic units being compared (county-based sampling stratum, state, or
HCFA region) in a linear regression. In these regressions, CAHPS“ ratings in reports serve as
dependent variables, sometimes in their original forms, sometimes dichotomized to correspond
to displays of data to consumers. Although age is very important for adjusting the rating of
Medicare, the most important CMA variables for within-MFFS CMA 2002-2004 were education
and self-rated mental health.
In MFFS-vs.-MA CMA these same variables from Table 1 also serve as
independent variables in a linear regression, but dummies correspond to MA plans, with MFFS
treated as an additional “plan.” While the direction of CMA coefficients are similar for MFFS
and MA, the magnitudes of the effects sometimes differ. In 2000- 2001, the well-established
tendency of healthier beneficiaries3 to rate their care more positively or to report better health
1
CMS data contain the indicator of state buy-in, which is a proxy for dual-eligibility status; state buy-in can exist for
an individual who is not actually on Medicaid
2
While proxy respondent status has only a small empirical effect on CMA, it has been included because many
stakeholders feel it is important for the face-validity of CMA.
3
As measured by general self-rated health
2
care experiences was considerably stronger in MA than in MFFS, with MA slopes generally 50
to 100% larger than MFFS slopes for the general self-rated health item for most subjective global
ratings and many objective report items. In other words, ratings and reports of one’s health care
were considerably more sensitive to one’s (general) health status in MA than it was in MFFS. In
2002-2004, this pattern was largely restricted to the global ratings. If this is a reliable trend, and
if one considers the report items to be more objective, one possible interpretation of these
findings would be that health-status based differences in MFFS and MA experiences may be
diminishing, though not the perceptions of those differences. Interestingly, the self-rated mental
health item did not follow this pattern- mentally healthier beneficiaries reported more positively
than less mentally healthy beneficiaries to the same extent in MFFS and MA, 2000-2004. In the
case of the global rating of Medicare or Medicare Advantage Plan, the tendency of the dually
eligible to be especially positive about Medicare was stronger than the tendency of the dually
eligible to be especially positive about Medicare Advantage. For three report items within the
Getting Needed Care composite and three report items within the Getting Care Quickly
composite, the dually eligible provided less favorable reports than others within MFFS, whereas
within MA dually eligible differed little or not at all from other beneficiaries.
A major implication of the difference in general health status coefficients is that the
difference between the case-mix adjusted mean of a MA plan and a FFS reporting entity depends
upon the reference population. Case-mix adjustment to a healthy reference population would be
relatively more favorable to MA, and case-mix adjustment to an unhealthy reference population
would be relatively more favorable to MFFS. In 2000-2004 Medicare Compare consumer
materials MFFS-vs.-MA CMA used the midpoint of MFFS beneficiary and MA beneficiary
characteristics as the reference population. Because of the generally poorer health status of
MFFS beneficiaries (even excluding the dually-eligible), the GHP component of CMA tends to
adjust in favor of MFFS relative to MA.
In comparing MFFS and MA, there was concern that underlying geographic factors not
captured in a case-mix model might inappropriately influence MFFS-vs.-MA comparisons. In
order to ensure geographic equivalence of state-level comparisons county-based “geographic
equivalence weights” were created (GEW) in the “states”4 where MA exists. These weights
were then combined with MFFS non-response weights.
Comparison weights have gone from moderate adjustments in favor of MA in 2001 to
very small adjustments 2002-2004. One interpretation is that MFFS sample was initially scarce
in the geographic regions that had the least positive Medicare experiences among those regions
with MA penetration. The shrinking effect of the comparison weights may be attributable to the
reallocation of MFFS sample into the counties with high MA penetration but low population that
were initially unrepresentative, in the efforts to reduce the comparison weights design effect. In
other words, the geographic distribution of the MFFS sample is much better matched to MA in
2004 than it was in 2001.
4 Including the District of Columbia and Puerto Rico
3
The impact of case-mix adjustment on Within-MFFS comparisons has remained
moderate. The adjustments for the most affected states are quite substantial for both betweenstate comparisons of MFFS and within-state comparisons of MFFS with MA. Nationally, casemix adjustment has gone from moderate adjustments in favor of MA in 2001 to small
adjustments in favor of MA in 2002 to moderate adjustments in favor of MFFS in 2003-2004. A
similar pattern exists for case-mix adjustment of state-level comparisons of MA and MFFS,
except that the amount of adjustment of these estimates by CMA has increased notably 20022004.
Adjustments favoring MA probably correspond to MA having a higher proportion of
certain types of negative responders: the young and the better educated. Adjustments favoring
MFFS probably correspond to MFFS having a higher proportion of a different class of negative
responders: the unhealthy. The shift from adjustments favoring MA to adjustments favoring
MFFS could mean that age and education selection into MA is becoming weaker or is being
dominate by stronger selection on the basis of health. Future research should investigate trends
in MFFS vs. MA case-mix demographics.
4
INTRODUCTION
The Medicare Fee-for-Service (MFFS) Consumer Assessment of Health Plans (CAHPS)
project surveys Medicare beneficiaries enrolled in the original Medicare health plan5 in order to
present information regarding their experiences to Medicare beneficiaries, state quality
improvement organizations (QIOs)6, and the Center for Medicare and Medicaid Services (CMS).
The goals of the project include:
1. Empowering beneficiaries to compare the experiences of those receiving FFS
Medicare and those receiving Medicare through MA plans available in their area, as
mandated by the Balanced Budget Act of 1997, and
2. Informing CMS and state QIOs about regional, state, and perhaps sub-state variation
in experiences with FFS Medicare.
A key component of these comparisons is appropriate case-mix adjustment. Case-mix
adjustment attempts to remove from ratings and reports of care response patterns that are
systematically associated with such patient-level characteristics as demographics, socioeconomic status, and general health status, which may vary considerably across reporting units.
These systematic patterns of association may reflect “response bias,” response patterns that do
not correspond to actual differences in quality of care.7 In any event, these are patient
characteristics that are generally agreed to be beyond the control of providers or plans once they
have been selected by beneficiaries. The goal of case-mix adjustment can therefore be thought
of as follows: to estimate the ratings and reports that a plan or collection of FFS providers would
have received if all providers and plans treated the same standardized population of patients
(Medicare beneficiaries). This adjustment should make attributions of ratings and reports to FFS
providers and MA plans more appropriate, supporting better decision-making by beneficiaries
and quality improvement by QIOs and CMS.
The Harvard team (see Cioffi, Cleary, et al., 2001) has conducted case-mix adjustment
analyses on three years of MA data prior to the initiation of MFFS data collection, and also
performed case-mix adjustment analyses on the MFFS field test data. In doing so, they devised
an analytic framework and associated terminology, which are well suited to the case-mix
adjustment of MFFS data discussed here. Their reports provide additional background on some
of the techniques used here, and the reader who is not familiar with these reports may want to
consult them when reading this report. Additional work on case-mix adjustment of CAHPS“
data may be found in Zaslavsky, Zaborski, et al. (2001), Elliott, Swartz, et al. (2001), Elliott,
Hambarsoomians, et al. (2001), and Elliott, Hambarsoomians, and Edwards (2002). Because of
the importance of coordinating MFFS and MA case-mix adjustment when comparing MA plans
to collections of MFFS providers, this report will parallel the approach and terminology of these
previous reports where appropriate. In addition, the selection of case-mix adjuster variables and
models for evaluation and comparison in this report draws on the findings established in these
5
These beneficiaries, plus those unsurveyed beneficiaries in the one Private Medicare FFS plan (Sterling), constitute
all beneficiaries not enrolled in MA plans.
6
Formerly peer review organizations (PROs).
7
It should be noted that case-mix methods cannot by themselves distinguish response bias from systematic
differences in actual health care experiences that are associated with the case-mix variables.
5
reports. In particular, this report will follow the structure of the 2001 MFFS Task 9 Report
(Elliott, Hambarsoomians et al, 2001).
Prior to the introduction of the MFFS survey, MA case-mix adjustment (CMA) had a
single focus: the adjustment of ratings and reports for comparison among MA plans. MFFS
case-mix adjustment now has two foci: (1) adjustment of collections of FFS providers for
comparison to MA plans and (2) adjustments of collections of FFS providers for comparison
with other FFS providers. This report will develop recommendations for both contexts, and will
refer to these contexts as MFFS-vs.- MA CMA and Within-MFFS CMA, respectively.
MFFS lacks a predefined reporting unit that is analogous to the plan in MA. The need to
define such a unit and the manner in which such a unit is defined has implications for both
reporting and CMA in MFFS. We will use the term reporting entity to refer to an aggregation of
providers for which CAHPS ratings and reports are reported. This term will thus apply to either
a plan in the case of MA or to a collection of FFS providers in the case of MFFS.8 Note that the
MFFS reporting entity can be a sub-state, state, or regional aggregation of FFS providers.
8
In the case of FFS, the aggregations of providers are based on geographically-defined, non-overlapping sets of FFS
beneficiaries. As beneficiaries may seek care outside of their unit of residence, the corresponding sets of providers
will be mostly, but not entirely, non-overlapping across units.
6
SUMMARY OF DATA AND VARIABLES
Data
The first (2000) national administration of the CAHPS MFFS survey involved the
administration of 168,000 surveys to MFFS beneficiaries: 3000 to beneficiaries residing in
Puerto Rico, and 165,000 to beneficiaries residing in the 50 states and the District of Columbia.
As described in the first report of geographic unit recommendations (Elliott, Solomon, Suttorp,
and Hays, 2000), the 165,000 United States surveys were administered to a stratified random
sample of MFFS beneficiaries, 600 each in 275 strata. These strata will be referred to as geo
units or MFFS Sampling Strata. These geo units are collections of counties and are entirely
contained within states (1 to 17 GU units in each state), are generally contiguous, and were
designed to avoid crossing Medicare Advantage Contract Area boundaries, Metropolitan
Statistical Area Boundaries, and Health Service Area boundaries where possible. The geo units
contain approximately equal numbers of MFFS beneficiaries (with under-sampling of
beneficiaries in 30 highly populous counties and over-sampling of non-MSA counties in 12
states being the major departures from proportionality), and were designed to potentially
function as reporting units as well as sampling strata. Of the 275 geo units, 205 had some MA
penetration.
As detailed in the RTI Team’s 2001 MFFS Operations Report, the 2001 sample design
involved an increased and reallocated sample size designed to maximize the precision of MFFSvs.-MA comparison within states and resulted in a higher response rate. As detailed in the RTI
Team’s 2002-2004 MFFS Operations Reports, the 2002-2004 sample designs involved further
iterative reallocations of sample to maximize the precision of MFFS-vs.-MA comparison within
states.
Variables
As detailed elsewhere, CAHPS reports consumer experiences in the form of four global
ratings (rated on a 0-10 scale, from worst possible to best possible) and five composites (each
composed of two to four report items, which are rated on a four-point ordinal scale from never to
always or on a three-point ordinal scale from not a problem to a big problem). Because CMA is
applied to individual report items before they are combined into composites, this report will
examine CMA of the four global ratings and the 21 report items, as summarized in Table 1
(adapted from Table III-3 in the 2000 MA Case-Mix Report).
Table 1: CAHPS ratings and composites
Variables
Description
Ratings
Health Plan
Rate your experience with your Medical health plan [Medicare]
Health Care
Rate all the health care you got in the last 6 months
Personal Doctor
Rate your personal doctor or nurse now
Specialists
Rate the specialist you saw most often in the last 6 months
7
Composites Report Items
x
Get Care Needed
x
x
x
x
Get Care Quickly
x
x
x
x
Doctor
Communicate Well
x
x
x
Office Staff
Courtesy
Paperwork, Info, &
Customer service
x
x
x
x
x
Easy to get a referral
Get necessary care
Easy to find doctor you happy with
Delays in care when waiting for approval
Get medical help through phone at doctor office
See doctor as soon as wanted
Get appointment as soon as wanted
Wait in doctor office/clinic for more than 15 minutes
Doctor listen carefully
Doctor explain things in ways can be understood
Doctor show respect
Doctor spend enough time
Office staff treat with courtesy and respect
Office staff helpful
Get info or help needed when call plan customer service
Find and understand written information
Have problem paperwork for health plan [Medicare]
Other survey variables and one administrative variable (dual eligibility) were considered
as case-mix adjusters (independent variables), as summarized in Table 2.
Table 2: Description of independent variables used in MFFS case-mix adjustment
Name (Dummies)
Description
Response Options
AGE (AGE44, AGE4564,
Age
<44, 45-64, 65-69, 70-74, 75AGE6569, AGE7579,
79, 80-85, >85
AGE8085, AGE85)
(above are 2002-2003 response
options; 2000-2001 response
(AGE64, AGE6569,
9
options were <65, 65-69, 70AGE7579, AGE80)
74, 75-79, and >79)
EDUC
Education
<8th grade, some high school,
(LESS8GRD, SOMEHIGH,
high school graduate or GED,
SOMECOLL, COLLGRAD,
some college (but less than 4
COLLMORE)
yr. Degree), 4 year college
graduate, >college graduate
(some graduate school beyond
the 4 year degree)
GHP
General health perception
Excellent, very good, good,
(EXCEL, VERYGOOD, FAIR,
fair, poor
POOR)
9
Exploratory 2001 analyses also broke down the under-65 age group into 18-39, 40-54, and 55-64 categories with a
variable called “AGE UNDER 65,” which coded these three subcategories linearly. This linear pattern was based on
preliminary analyses. See Appendix C.
8
MHP
(MHEXCEL, MHGOOD,
MHFAIR, MHPOOR)
RPCS1210
RMCS1211
(PROXY, ANSPROXY)
DUALELIG12
Mental health perception
Excellent, very good, good,
fair, poor
SF-12 physical composite
score; includes MHP item.
SF-12 mental composite score;
includes MHP item.
Proxy respondent status
Mixed response options
converted to standardized score
Mixed response options
converted to standardized score
No assistance on survey,
someone helped but did not
answer for you, someone
answered for you
Yes, no
Dual-eligibility indicator
(eligible for Medicaid
program)
Finally, three sets of FFS reporting entities were considered. The dummy variables used
for these purposes were 276 geo unit indicators (one omitted), 51 state/district/territory
indicators13 (one omitted), and 9 CMS region indicators (one omitted). A list of the states
constituting each of the 10 CMS regions appears as Table 3. Geo unit, state, and CMS region
indicators were also used to create interaction terms for the evaluation of assumptions of the
homogeneity of effects of case-mix adjusters across reporting entities.
Table 3: States comprising CMS Regions
Region Number
CMS Region
1
Northeast (MA,ME,VT,CT,RI,NH)
2
NY/ NJ/Puerto Rico
3
Mid-Atlantic (PA,DE,DC,MD,VA,WV)
4
S. Atlantic (AL,FL,GA,KY,MS,NC,SC,TN)
5
Mid-West (IL,MN,OH,WI,MI,IN)
6
Southwest (AR,OK,TX,LA,NM)
7
Central (KS,MO,IA,NE)
8
West (CO,MT,ND,SD,UT,WY)
9
Pacific (CA,AZ,HI,NV)
10
Northwest (AK,ID,OR,WA)
10
Not used in 2000.
Not used in 2000.
12
CMS data contain the indicator of state buy-in, which is a proxy for dual-eligibility status; state buy-in can exist
for an individual who is not actually on Medicaid.
13
Hereafter called state indicators for brevity, but also applicable to the District of Columbia and Puerto Rico.
[number of states varied from year to year]
11
9
GENERAL ANALYTIC APPROACH
In this report, CMA involves linear regression models with global ratings and reports of
care serving as dependent variables and with beneficiary-level characteristics serving as
independent variables (case-mix adjusters).14 As noted in the 2000 MA CMA Report, one can
describe this model as follows for a single outcome i:
y ipj
where
E ic xipj P ip H ipj
y ipj
represents the response to [outcome] i of respondent j from [reporting entity]
x
p …, E i is a regression coefficient vector, ipj is a covariate vector … [containing case-mix
P ip
H ipj
adjusters],
is an intercept parameter for [reporting entity] p, and
is the error term.
Because all between-[reporting entity] effects are absorbed into the dummy variable
coefficients, the E i coefficients represent within-[reporting entity] effects of the adjuster
P
variables. The adjusted [reporting entity] ratings correspond to the dummy variable effects ip .
The adjusted ratings (after centering) can be interpreted as the ratings we would expect for each
[reporting entity] if every [reporting entity] had the same distribution of patient-level variables (
i.e. equivalent mixes of patients).
Because MFFS has no natural reporting entity corresponding to the plan in MA, there are
several choices for reporting entity: geo unit, state, or CMS region. The choice of reporting
entity in MFFS will determine how much geographic variation is “absorbed” into the intercept
vector in the above model and how much is left to be attributed to case-mix adjusters. Because
geo units are entirely nested within states and states are entirely nested within CMS regions, the
smaller reporting entities will absorb at least as much variation as the larger reporting entities. To
the extent that case-mix adjusters vary geographically in their values, the choice of reporting
entity will affect the magnitude of the coefficients estimated in MFFS CMA.
Assumptions of CMA
In order for case-mixed adjusted means to have the interpretation discussed above, a
number of assumptions must be met. A first assumption is that the case-mix adjusters are not
endogenous. This assumption means that the values of the case-mix adjusters are not
substantially influenced by actions of the providers or by beneficiaries’ experiences with
providers. This assumption is not easily testable in cross-sectional studies. This report will not
attempt to independently establish the exogeneity of the case-mix adjusters employed, but will
instead restrict consideration to the variables in Table 2, for which there is general consensus
14
For the one dichotomous item an analogous logistic regression is used.
11
regarding an absence of serious endogeneity in the context of case-mix adjustment of health care
data.
A second assumption is that the case-mix adjusters are linear in their effects on the
outcomes to which they are applied. This assumption is applicable to ordinal and continuous
case-mix adjusters, and is empirically verifiable.
A third assumption is that the effects of case-mix adjusters are homogenous across the
reporting entities being compared. This assumption can be verified empirically through the
use of interaction terms in linear models, and is specific to the set of reporting entities being
compared.
Desirable Properties of CMA Models
There are three properties that a good MFFS CMA model would possess: (1) precision,
(2) parsimony, and (3) robustness across applications. The criterion of precision means that
there is strong evidence that the case-mix adjustment variables are truly associated with ratings
and reports, and that the magnitude of these associations is well estimated. The criterion of
parsimony means that the model is as simple as possible without sacrificing explanatory power.
In other words, variables that add to model complexity without adding to model impact are
excluded. The criterion of robustness across applications means that the model selected is
appropriate across the variations in reporting formats to which it is applied.
The criterion of precision requires that case-mix adjusters have statistically significant
effects and that the ratio of estimated parameters to their standard errors (t-statistics) be large.
Implementing the criterion of parsimony requires a definition of explanatory power. We
will use the E.P. (explanatory power) statistic, a unitless measure of the impact of a case-mix
adjuster developed by the Harvard team in the context of MA CMA (Cioffi, Clearly, et al.
2001). Briefly, the impact of a case-mix adjuster on adjusted scores is a product of two
quantities: (1) the proportion of the variance of the outcome explained by the case-mix adjuster
in an individual-level regression (incremental change in R-sq) and (2) the variance in mean
levels of the case-mix adjuster across reporting entities. The formula for E.P. is:
E.P. = Var(Reporting Entity)/Var(Error) * (net increment in R-sq)
The derivation of this formula may be found in the MA Case-Mix Report. Because values
for E.P. tend to be very small, we will follow the convention of presenting E.P. * 1000.
Parsimony requires selecting the simplest model that accounts for most of the explanatory power
possible with more elaborate models.
Adjusted ratings and composites are presented in a number of different formats, and at
different levels of aggregation. It is desirable that a CMA model be applicable across this variety
of contexts and that its effects be reasonably consistent across these applications. The linear
models presented here treat the 11-point global ratings and the 3- and 4-level ordinal scales as
continuous variables, computing means. This approach maximizes the statistical power available
12
to compare CMA models and also corresponds to the format in which adjusted ratings and
composites may be presented to CMS, state QIOs, and researchers. On the other hand,
dichotomized presentations of these same ratings and composites will be presented to
consumers.15 It is desirable that CMA models behave similarly with these dichotomized
outcomes. Likewise, reporting entities will be states for some applications and presentations, but
may be geo units or CMS regions for other applications and presentations. It is desirable that
CMA models behave similarly across these contexts.
Imputation of Missing Values for CMA Variables
The potential CMA variables listed in Table 2 exhibited low rates of item missingness in
the 2000-2004 MFFS data. Nonetheless, case-wise deletion (omission of all cases with any
missing values on CMA variables) would likely lead to bias in estimates of CMA models.
Previous MA CMA reports have used simple mean imputation within MA plan for missing
values of CMA variables (replace missing values for CMA variables with the mean non-missing
value within the MA plan in question). In order to maximize comparability with this approach,
we use simple mean imputation within geo units for MFFS, as was the case in the 2000-2003
MFFS Reports (replace missing values for CMA variables with the mean non-missing value
within the geo unit in question). Given the low rates of item missingness observed for CMA
variables, we feel that the results obtained here are likely to be quite similar to those that would
have been obtained with more complex imputation methods, such as model-based imputation.
No imputation of outcomes (global ratings and report items) is performed, and no imputation is
used in cases of unit non-response (an incomplete or unusable survey).
15
Global ratings will be dichotomized 10 vs. 0-9; reports will be dichotomized such that the most favorable ordinal
response will constitute a single category.
13
SUMMARY OF MFFS PILOT TEST CASE-MIX ADJUSTMENT REPORT
The Harvard team performed a CMA analysis for the MFFS-CAHPS Pilot Test using
data from 1,931 MFFS beneficiaries from a highly diverse but limited number of geographic
areas and compared results to those obtained from 1997 and 1998 MA beneficiaries matched on
residential location. They considered a base model that was the same model that has been
recommended in the MA CMA Reports, as well as several alternatives. The base model includes
age, education, general health perception, and proxy status, all coded categorically (one dummy
per response option, other than a single omitted level). In the Pilot Test, coefficients for the base
model were generally similar for MA and MFFS. Gender, activities of daily living (ADL),
instrumental activities of daily living (IADL), and variables based on zip codes did not
consistently add explanatory power to the base model. Among those variables present on the
MFFS instrument but absent from the MA instrument, items related to mental health stood out as
adding substantially to the explanatory power of the base model. While both the single item,
five-level Mental Health Perception (MHP) item and the 12-item SF-12 Mental Health
Composite (RMCS12) had substantial additional explanatory power, the single item was
recommended over the latter for reasons of simplicity and the potential for future reductions in
survey length.
15
OVERVIEW OF 2004 CASE-MIX REPORT
For readers familiar with the 2000-2003 (Years 1-4) Case-Mix Reports, we will briefly
describe how this report differs from the previous year’s report. First, this report seeks to
evaluate the stability of many of the findings and resultant decisions from the 2000-2003 CaseMix Reports, including the choice of case-mix adjusters, their parameterization, and their impact.
Second, we have reformatted the presentation of information in a way that favors comparative
tables across years were possible and which relegates older data to the Appendix when this is not
possible, with the hopes of producing a more concise document. In particular, new Figures 1-4
summarize the stability of case-mix coefficients across the five years of the project and a new
section that follows provides a global summary of five years of findings. Third, Appendix D has
been expanded to provide a more thorough examination of the current life satisfaction item on
subgroup comparisons. Throughout this report, “statistically significant” will indicate a p-value
of less than 0.05 with a 2-sided test.
17
OVERVIEW OF 2000-2004 CASE-MIX FINDINGS AND TRENDS
Case-mix adjusters had consistent coefficients within MFFS over the five years of the
project (see Table 10, Figures 1-4, Appendix A and Appendix E), especially education and selfrated mental health. Case-mix coefficients for the rating of Medicare were less stable than those
for other ratings. These patterns have been consistently non-linear (see Table 4), suggesting that
they are best parameterized categorically. The tendency of health status to be predictive of more
positive global ratings has been consistently stronger within MA than within MFFS (see Table
5.2). A similar pattern for report items in the first few years of the project has largely
disappeared. The rating of mental health status is the one case-mix adjuster that has been
consistently comparable between MFFS and MA. Whereas the case-mix coefficients initially
exhibited substantial regional variation within MFFS, they are now quite consistent across
regions, with the exception of coefficients for the global rating of Medicare (see Tables 6 and 7).
In terms of explanatory power, education and mental health ratings have been the most
consistently important case-mix variables (see Tables 8a and 8b). Age and overall health rating
have been the next most important among those variables employed in the final models. Among
those variables not included in final models, current life satisfaction and phone versus mail mode
would have relatively large impacts if they were included, both having a greater potential impact
than overall self-rated health.
Education and self-rated mental health appear to have a variety of properties that are
superior to those exhibited by overall self-rated health and age. The variability of CMA patterns
for the rating of Medicare suggests that this measure may be more of a barometer of the
popularity of the Medicare program, subject to media and other influences, than a direct measure
of health care experiences.
It could be argued that both age and overall self-rated health are CMA variables that have
been retained through historical precedence and are no longer as important as they once were,
given the addition of self-rated mental health to the CMA model. Given that these variables also
are much less stable over time, delivery system, and geography than self-rated mental health and
education, it could be argued that an appealing and more parsimonious CMA model might drop
overall self-rated health and age as adjustment factors. Doing so could have the appeal of better
distinguishing true differential experiences by age and health status from patterns of response
tendency.
The impact of Within-MFFS CMA is moderate (15-44% of the standard deviation of the
unadjusted geounit means), but not negligible (largest geo-unit adjustments are 0.4-1.6 such
standard deviations; see Table 11). Among the ratings, adjustments are largest for the rating of
Medicare and smallest for the rating of Personal Doctor. The magnitude of these impacts has
been similar from year to year.
At the state level, the mean absolute Within-MFFS case-mix adjustment is 17-44% of a
state level standard deviation for the two ratings and three composites reported on Medicare.gov,
with the largest state adjustments being three to five times that large. The magnitude of these
adjustments has been similar from year to year as well (see Table 12).
18
For national MFFS-vs.-MA comparisons (see Table 13), comparison weights have gone
from moderate adjustments in favor of MA in 2001 to very small adjustments 2002-2004. One
interpretation is that MFFS sample was initially scarce in the geographic regions that had the
least positive Medicare experiences among those regions with MA penetration. The shrinking
effect of the comparison weights may be attributable to the reallocation of MFFS sample into the
counties with high MA penetration but low population that were initially underrepresented, in the
efforts to reduce the comparison weights design effect. In other words, the geographic
distribution of the MFFS sample is much better matched to MA in 2004 than it was in 2001.
For the same national comparisons, case-mix adjustment has gone from moderate
adjustments in favor of MA in 2001 to small adjustments in favor of MA in 2002 to moderate
adjustments in favor of MFFS in 2003-2004. Adjustments favoring MA probably correspond to
MA having a higher proportion of certain types of negative responders: the young and the better
educated. Adjustments favoring MFFS probably correspond to MFFS having a higher
proportion of a different class of negative responders: the unhealthy. The shift from adjustments
favoring MA to adjustments favoring MFFS could mean that age and education selection into
MA is becoming weaker, but health selection is becoming stronger.
The MFFS non-response and design weights were more important than the comparison
weights, but less important than case-mix adjustment in 2002-2004.
Within-state case-mix adjustment of MFFS-vs.-MA differences had an average withinstate effect of 0.7-2.8% in 2004 (see Table 14). These adjustments are generally larger than in
2003 and are represent a substantial increase in impact since 2001-2002 for three measures
(Doctor Communication, Medicare Rating, and Health Care Rating). These 2004 adjustments are
27-67% of the standard deviation of the state-to-state variation in the MFFS-MA difference. The
largest adjustments were 1.7-7.5%. The case-mix adjustment effects were in favor of MFFS in
almost all cases in 2003-2004. In 2004, there were three measures (again Doctor
Communication, Medicare Rating, and Health Care Rating) for which all states were adjusted in
favor of MFFS. In contrast, 2001-2002 adjustments were not only smaller, but were in favor of
MA more often than not.
The 2002-2004 increase in state-level CMA adjustments in favor of MFFS, reflected in
both consistency and magnitude, cannot easily be explained by a corresponding trend in the
explanatory power of the CMA model at the individual level. Rather, it suggests that within-state
selection on characteristics related to CMA models (health, age, education) is becoming stronger.
It is likely that the tendency of MA beneficiaries to be healthier than MFFS beneficiaries within
states has become stronger over 2002-2004, and the CMA model is making greater adjustments
in favor of MFFS to account for this trend.
19
DISTINCTIONS BETWEEN MFFS-VS.-MA CMA AND WITHIN-MFFS CMA
The primary purpose of MFFS-vs.-MA CMA is to facilitate unbiased comparison of
beneficiary experiences with MFFS and MA for those beneficiaries with a choice between MFFS
and MA. Dually eligible Medicare beneficiaries (those also eligible for Medicaid) present a
challenge for this comparison, because some Medicaid regulations may have discouraged MA
enrollments in some states. This was reflected by the fact that the proportion of dually eligible
beneficiaries in MA is far less than the 11% observed in the 2000 MFFS sample and in the
corresponding MFFS population. Because the dually eligible were thought to differ from other
Medicare beneficiaries in ways that might not have been adequately be captured by CMA, dually
eligible beneficiaries were excluded from MFFS-vs.-MA comparisons and CMA models 20002003. In 2004, joint discussion by the MA and MFFS teams resulted in the conclusion that the
MA environment had changed in such a way that it was now unlikely that the dually eligible
selected plan types in a way that could not be captured by CMA. As a consequence, the dually
eligible were included in 2004 MFFS-vs.-MA comparisons, and a dually eligible indicator was
added to this corresponding CMA model. The primary purposes of Within-MFFS CMA are (1)
to facilitate assessment of geographic variation in MFFS experiences and (2) to facilitate
comparison of MFFS experiences among subgroups of beneficiaries by controlling for the effects
of exogenous case-mix adjusters. The latter goal may require that case-mix adjusters be used as
covariates in a regression or Analysis of Covariance (ANCOVA) model, rather than being used
to explicitly adjust means of reporting entities. Because the dually eligible constitute a sizable
proportion of the MFFS population, dually eligible beneficiaries were included in Within-MFFS
CMA models 2000-2004 along with indicator of dual eligibility.
21
TESTING MODEL ASSUMPTIONS FOR CMA
The following sections present the results of tests of model assumptions.
Linearity
Table A1a in Appendix A reports the coefficients for the base model from the MFFS
Pilot Test recommendations, estimated on the full 2000 MFFS data set, excluding the dually
eligible, and using geo units as the reporting entity/intercept vector. Case-mix adjusters are
specified as dummies. Tables A1b and A1c report the coefficients for the same model, estimated
on the full 2001 and 2002 MFFS datasets, respectively, excluding the dually eligible, and using
geo units as the reporting entity/intercept vector. Tables A3b (2001 data) and A3c (2002 data)
are similar to Tables A1b and A1c, respectively, except that MHP dummies are added to the
model. Examination of the coefficients in these tables reveals general patterns similar to those
that have been observed in the past in MA: greater age, less education, better general perceived
health, and no proxy assistance are associated with more favorable ratings and reports. These
patterns are fairly consistent across global ratings and report items, although education is not
always consistent in 2002 data. Table A3d (2003 data) is similar to Tables A3b (2001 data) and
A3c (2002 data.) Table A2e (2004 data), is only different from A3d in that the data include
dually eligible beneficiaries and the regression model an indicator for those cases. If these
ordinal items had linear effects on the outcomes, the coefficients would be both monotonic and
approximately evenly spaced, such that the intervals for one unit changes in the ordinal variable
(including the implicit coefficient value of 0 for the omitted category) are all approximately
equal. As can be seen, while the monotonicity usually holds, the even spacing does not. In the
case of age, the difference between those under 65 (disabled) and those 65 to 69 years of age is
generally much greater than between any other two adjacent age categories prior to the
introduction of subcategories of age less than 6516. Since this change was made, a further nonlinearity persist in 2002: the differences between age categories decreases as age increases; in
particular, the effect of age appears to taper beyond age 79. In the case of education, there is a
small but fairly consistent departure from monotonicity: those with some high school education,
but without a high school degree, provide the most favorable ratings and reports. Their ratings
and reports are generally more favorable than those with more or less education.17
Table 4 reports the results of partial F-tests of the null hypothesis of linearity for the
coefficients in Tables A1a (2000 MFFS), A3b (2001 MFFS), A3c (2002 MFFS), A3d (2003
MFFS) and A2e (2004 MFFS) against the alternative that the dummy coded categories explain
significant additional variance. Highlighted cells within Table 4 correspond to significant
evidence against linearity of the ordinal CMA categories. As can be seen, strong evidence
against the assumption that the ordinal forms of education, age, and mental health perception
have linear effects in at least four of five years (three of four years for mental health perception)
for all four global ratings. There is similar evidence against the linearity of general health
perception for at least one global rating for all five years. A high proportion of report items also
16
The under 65 group differs from other age categories both in its much higher level of disability and in the greater
age range contained.
17
This holds less consistently in 2002 than in previous years
22
evince violations of the assumption of linearity. These results have led to the categorical
parameterization of education, age, GHP, and MHP (since 2001) in 2000-2004 MFFS analyses.
Table 4: F-Statistics for the Null Hypothesis of Linearity of Ordinal Case-Mix Adjusters, Global
Ratings, 2000 – 2004
F-Statistics, by Case-Mix Adjuster
Education
Case-Mix Adjuster:
Survey Year:
Age
2000a
2001
2002
2003
2004b
2000a
2001
2002
2003
2004b
41.00
82.12
35.62
27.06
8.43
82.12
80.68
69.89
57.15
25.78
11.68
21.23
15.63
28.80
13.22
11.11
7.48
18.36
19.61
23.42
5.78
7.93
9.62
10.45
12.26
24.74
40.49
47.51
35.18
29.57
4.34
5.59
4.25
10.56
3.99
0.94
6.30
8.16
17.17
16.37
Rating Description
Medicare
Health Care
Personal Doctor
Specialist
F-Statistics, by Case-Mix Adjuster
General Health
Case-Mix Adjuster:
Survey Year:
Mental Health
2000a
2001
2002
2003
2004b
2000a
2001
2002
2003
2004b
6.16
1.39
2.74
3.16
0.95
NA
9.86
5.82
1.49
3.19
6.29
2.29
0.70
0.99
2.02
NA
24.04
6.85
5.41
5.89
20.27
8.24
8.16
4.69
2.89
NA
35.60
11.42
17.18
26.8
0.23
1.43
1.81
0.42
0.84
NA
9.68
7.62
5.11
10.45
Rating Description
Medicare
Health Care
Personal Doctor
Specialist
a
Model does not include MHP case-mixed adjuster.
b
Sample includes dually eligible beneficiaries, and regression model includes an indicator for these cases.
23
Homogeneity for MFFS-vs.-MA CMA
Traditional CMA assumes homogeneity of effects for the case-mix adjusters across the
reporting entities being compared. In the context of MFFS-vs.-MA CMA, this translates into an
assumption that the coefficients of case-mix adjusters are similar within MA and MFFS. While
the MFFS Pilot Test CMA Report found no evidence of a difference in these coefficients, the full
2000 MFFS data provide much greater statistical power to detect such differences.
Table 5.1 compares the magnitude of the effects of case-mix adjusters (including
indicator for dually eligible beneficiaries) for MFFS and MA for the four global ratings and 15
report items comprising four reported composites in 2004 data. Tables E1a (2000), E1b (2001),
E1c (2002) and E1d (2003) of Appendix E are based on similar analyses with the exception of
omission of dual eligibility beneficiaries. Table 5.1 was based on a model containing age,
education, GHP, MHP, proxy status, dual eligibility indicator and intercepts (dummies) for
geographical units (for the MFFS sample) and plans (for the MA sample). Table 5.2 summarizes
patterns across the five years.
To facilitate comparison of coefficients between MFFS and MA, age, education,
GHP, and MHP were parameterized linearly here, allowing the patterns of categorical slopes to
be summarized with a single number. To facilitate comparisons of the magnitude of CMA
coefficients across reports and global ratings, results are standardized so that they represent
standard deviations of the outcome per ordinal level of the adjuster. Instances in which MFFS
and MA coefficients differ significantly (p<0.05) are highlighted in these tables. The data used to
produce these tables represent the common states with both MFFS and MA (excluding dual
eligible cases in 2000 - 2003.)
The most striking pattern in Table 5.1 (and Table 5.2) is the steeper slope for GHP in MA
than in MFFS for all four global ratings and one of 15 report items. This is consistent with the
previous four years, during which GHP slopes had been significantly steeper in MA than in
MFFS for at least three of four global ratings and one to five of 15 report items. MHP slopes
have never differed significantly between MA and MFFS for any outcomes. Education and age
have shown a few differences in slopes over the first five years, most in the direction of steeper
slopes within MA. In 2004, we notice steeper slopes for dual eligibility in MFFS compared to
MA for one global outcome and six of 15 report items. In the case of the global rating of
Medicare or Medicare Advantage Plan, the tendency of the dually eligible to be especially
positive about Medicare was stronger than the tendency of the dually eligible to be especially
positive about Medicare Advantage. For three report items within the Getting Needed Care
composite and three report items within the Getting Care Quickly composite, the dually eligible
provided less favorable reports than others within MFFS, whereas within MA dually eligible
differed little or not at all from other beneficiaries.
Table 5.1: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2004)
STANDARDIZED COEFFICIENTS
AGE
EDUCATION
GHP
MHP
Dual Eligible
(7 levels)
(6 levels)
(5 levels)
(5 levels)
(Indicator)
24
FFS
GLOBAL (scale 0=worst – 10=best)
How would you rate your
personal doctor now
0.02
How would you rate your
specialist now
0.03
Rate overall healthcare, past
6 months
0.05
Rate all experience with
Medicare/health plan
0.14
GETTING NEEDED CARE (scale 1-4)
Was it a problem getting your
choice of doctor
0.04
6 mo: Problem getting
referral to specialist
0.04
6 mo: Problem getting care
needed
0.03
6 mo: Problem waiting for
plan approval
0.09
MA
FFS MA
FFS MA
FFS MA
FFS MA
0.03
-0.06 -0.06
-0.02 -0.06 *
-0.09 -0.08
0.07 0.11
0.02
-0.04 -0.05
-0.03 -0.06 *
-0.11 -0.11
-0.03 0.03
0.03
-0.06 -0.07
-0.09 -0.13 *
-0.12 -0.11
-0.02 0.04
0.07 *
-0.07 -0.07
-0.06 -0.12 *
-0.08 -0.08
0.34 0.13 *
0.04
-0.05 -0.06 *
-0.06 -0.10 *
-0.05 -0.04
-0.15 0.02 *
0.04
-0.02 -0.01
-0.07 -0.08
-0.06 -0.05
-0.23 -0.08 *
0.03
-0.01 -0.01
-0.07 -0.08
-0.06 -0.06
-0.21 -0.11 *
0.06
-0.04 -0.05
-0.09 -0.10
-0.06 -0.04
-0.25 -0.09
-0.04 -0.05
0.05 0.03
-0.09 -0.08
-0.08 -0.06
0.14 -0.00
0.04 -0.00
CONSUMER SERVICE, INFORMATION, AND PAPERWORK (scale 1-4)
6 mo: Problem getting help
from customer service
0.03 0.03
-0.03 -0.06
-0.07 -0.06
6 mo: Problem understanding
materials
0.01 0.03
0.02 -0.02 * -0.08 -0.10
6 mo: Paperwork problems
0.04 0.03
-0.03 -0.05
-0.07 -0.06
GETTING CARE QUICKLY (scale 1-5)
6 mo: Got help/advice needed
0.03 0.02
6 mo: Saw doctor wanted for
routine care
0.02 0.02
6 mo: Got care as soon as
wanted
0.03 0.04
6 mo: Taken to room within
15 minutes
-0.01 -0.01
DOCTOR COMMUNICATION (scale 1-5)
6 mo: Doctor listened
carefully
0.03 0.02
6 mo: Doctor explained well
-0.01 -0.02
6 mo: Doctor showed respect
to you
0.02 0.02
6 mo: Doctor spent enough
time with you
0.01 0.01
-0.04 -0.03
-0.08 -0.09
-0.09 -0.08
-0.12 0.02 *
-0.05 -0.03
-0.08 -0.07
-0.09 -0.08
-0.06 0.02
-0.02 -0.02
-0.06 -0.08
-0.08 -0.07
-0.12 0.00 *
-0.00 0.01
-0.07 -0.06
-0.05 -0.05
-0.08 0.01 *
-0.05 -0.04
-0.03 -0.02
-0.08 -0.09
-0.09 -0.11
-0.09 -0.09
-0.11 -0.11
-0.01 -0.00
0.02 -0.01
-0.03 -0.03
-0.08 -0.10
-0.10 -0.10
-0.01 0.00
-0.05 -0.05
-0.09 -0.11
-0.10 -0.10
0.01 -0.01
if |MA beta| > |ffs beta|
if |ffs beta| > |MA beta|
if |ffs beta| = |MA beta|
25
Table 5.2: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA (Years 2000-2004)
Case-Mix Adjuster:
Age
Education
GHP
1
Survey Year: 2000 2001 2002 2003 2004
2000
2001
2002
1
2003 2004
1
2000 2001 2002 2003 2004
2000 2001 2002 2003 20041
Rating Description
GLOBAL (scale 0=worst – 10=best)
How would you rate your
personal doctor now
How would you rate your
specialist now
Rate overall healthcare, past 6
months
Rate all experience with
Medicare/health plan
NA
NA
NA
NA
GETTING NEEDED CARE (scale 1-4)
Was it a problem getting your
choice of doctor
6 mo: Problem getting referral
to specialist
6 mo: Problem getting care
needed
6 mo: Problem waiting for plan
approval
NA
NA
NA
NA
CONSUMER SERVICE, INFORMATION, AND PAPERWORK (scale 1-4)
6 mo: Problem getting help
from customer service
6 mo: Problem understanding
materials
6 mo: Paperwork problems
NA
NA
NA
GETTING CARE QUICKLY (scale 1-5)
6 mo: Got help/advice needed
NA
6 mo: Saw doctor wanted for
routine care
6 mo: Got care as soon as
wanted
NA
NA
26
MHP
6 mo: Taken to room within 15
minutes
NA
DOCTOR COMMUNICATION (scale 1-5)
6 mo: Doctor listened carefully
NA
6 mo: Doctor explained well
NA
6 mo: Doctor showed respect to
you
6 mo: Doctor spent enough
time with you
NA
NA
if |MA beta| > |ffs beta|
if |ffs beta| > |MA beta|
if |ffs beta| = |MA beta|
1
Sample includes dually eligible beneficiaries; regression models include an indicator for dual eligibility.
27
A major implication of this heterogeneity in GHP slopes is that the difference between
the case-mix adjusted mean of a MA plan and a FFS reporting entity depends upon the reference
population. For example, because the effect of health status is stronger for MA than for MFFS
(the slope is steeper in a linear approximation), and because better health status is associated with
better ratings and reports, case-mix adjustment to a healthy reference population would be
relatively more favorable to MA, and case-mix adjustment to an unhealthy reference population
would be relatively more favorable to MFFS.
There are at least three approaches to dealing with the heterogeneity of case-mix effects
for MFFS-vs.-MA CMA: (1) stratification, (2) estimation of pooled CMA coefficients, and (3)
independent estimation of CMA coefficients for MFFS and MA, with adjustment to the midpoint
of MFFS and MA population means. See Elliott, Swartz, Adams, Spritzer, and Hays (2001) for
additional discussion of this topic.
Stratification would attempt to divide beneficiaries into subgroups (on the basis of health
status or other variables), such that remaining case-mix variables had essentially homogenous
effects within subgroups. While this approach potentially offers very targeted and informative
comparisons, additional research regarding (1) the best way to stratify from a statistical
perspective and (2) the implications of reporting stratified ratings and reports on consumer
comprehension would need to be completed before this approach could be recommended.
Stratified reporting would require “drill-down” capability, so that targeted information could be
shown to beneficiaries for their stratum only, or would require multiple displays of information.
Case-mix adjustment would occur within these strata, using variables not involved in the
stratification.
The estimation of pooled CMA coefficients essentially ignores the heterogeneity by
forcing common coefficients across MA and MFFS. This approach has at least two difficulties:
(1) the relative weighting of MFFS and MA in determining the coefficients is somewhat
arbitrary18 and (2) comparisons among MA plans are adjusted not on the basis of how case-mix
adjusters function within MA, but partially on the basis of how these variables function within
MFFS19.
Independent estimation of CMA coefficients for MFFS and MA has the advantage of
allowing more appropriate adjustment of comparisons within payment type (MA or MFFS).
Furthermore, if the reference population to which both payment types are adjusted is the
midpoint of the mean vectors of the two payment types on case-mix adjuster variables, the
amount of adjustment is the same as would have been produced by pooled estimation of CMA
coefficients. For these reasons, this third approach to case-mix heterogeneity (independent
estimation) was chosen for 2000-2004 data and is recommended in future analysis.
The steeper slope for GHP within MA has been consistent for global ratings over 20002004. On the other hand, the number of report items for which the GHP slope is steeper in MA
18
Without intervention, coefficients would be weighted by the relative sample sizes of the MFFS and MA surveys.
Additional weighting could make the relative contributions of MFFS and MA proportionate to their prevalence in
the population, but that would decrease the precision of the estimated coefficients.
19
The second difficulty could be eliminated only if one were willing for the case-mix adjusted MA overall mean to
be different when comparing within-MA and when comparing to MFFS.
28
has dropped from four to five items in 2000-2001 to one to two items in 2002-2004. If this is a
reliable trend, and if one considers the report items to be more objective, one possible
interpretation of these findings would be that health-status based differences in MFFS and MA
experiences may be diminishing, but not the perceptions of those differences.
Homogeneity for Within–MFFS CMA
Homogeneity of the effects of case-mix adjusters across reporting entities is an
assumption behind the comparison of MFFS experiences across reporting entities. To the extent
this assumption does not apply, caution must be exercised when interpreting differences in casemix adjusted means in reports and ratings across MFFS reporting entities. MA CMA reports
have found evidence of statistically significant heterogeneity in case-mix coefficients across the
ten CMS regions. A similar finding in MFFS would pose some difficulties when CMS regions
were used as reporting entities.
The 2000 MA CMA Report tested for regional interactions among case-mix adjusters by
starting with the standard base model (with the standard dummy specifications of ordinal casemix adjusters) plus CMS region dummies, and then testing the additional variance contributed by
the interactions of CMS region dummies with linear specifications of the ordinal case-mix
adjusters in the base model (using a partial F-test). A similar approach was followed here for
MFFS. 20
Table 6 presents the p-values for these partial-F tests for MFFS for the four global ratings
for 2000- 2004. Highlighted cells indicate statistically significant variation in CMA coefficients
by CMS regions. In addition to the base model, the 2001-2004 models included MHP and its
interactions with CMS regions, and the 2004 models additionally include dual eligibility
indicator and its interactions. In 2000 MFFS, there was clear evidence of heterogeneity by CMS
region for GHP and age, but no evidence of heterogeneity for education and proxy status. These
results were similar to those found in 2000 MA data. In 2001 MFFS data, GHP still shows
heterogeneity by region, but age only does for ratings of specialists, and the remaining three
variables are inconsistent in their results. In 2002 MFFS data we see consistent heterogeneity by
CMS region for age and education, but regional heterogeneity only in some cases for GHP,
MHP, and proxy status. In 2003, we only observe two instances of heterogeneity by CMS
regions: rating of Medicare for age and rating of Health Care for age. Overall age has exhibited
the most heterogeneity across CMS regions within MFFS. GHP exhibited a large amount of
regional heterogeneity in 2000-2002. However, in 2003 and 2004 GHP is no longer
heterogeneous among the CMS regions. The rating of Medicare exhibits the most heterogeneity
with significant test results for age, proxy status, and duel eligibility in 2004. This may reflect
strong regional variations in views of the Medicare program. Finally, the overall amount of
regional heterogeneity in case-mix adjusters has decreased over the five years of the project.
20
Categorical, rather than linear interactions were used for proxy status.
29
Table 6. P-values for partial F-tests of heterogeneity of Within-FFS Case-Mix Effects by CMS
by Region, Years 2000-2004
F-Statistics, by Case-Mix Adjuster
Global Rating:
Medicare
Health Care
20001
2001
2002
2003
20042
20001
2001
2002
2003
20042
General Health
0.02
<.01
0.74
0.05
0.71
0.08
0.01
0.02
0.90
0.18
Age
<.01
0.49
<.01
<.01
<.01
0.00
0.23
<.01
0.02
<.01
Education
0.45
0.10
0.02
0.16
0.42
0.27
0.03
0.22
0.77
0.31
Proxy
0.14
0.06
0.44
0.66
<.01
0.32
0.10
0.04
0.56
0.90
Mental Health
NA
0.00
0.01
0.54
0.35
NA
0.81
0.03
0.41
0.47
Dual Eligible
NA
NA
NA
NA
<.01
NA
NA
NA
NA
0.13
Survey Year:
Case-Mix Adjuster
F-Statistics, by Case-Mix Adjuster
Global Rating:
Personal Doctor
Specialist
20001
2001
2002
2003
20042
20001
2001
2002
2003
20042
General Health
0.01
0.62
0.67
0.50
0.35
0.02
0.01
0.50
0.91
0.46
Age
0.01
0.36
0.04
0.33
0.15
0.03
0.04
0.01
0.31
0.09
Education
0.49
0.07
0.00
0.59
0.11
0.69
0.78
0.01
0.52
0.46
Proxy
0.56
<.01
0.02
0.78
0.33
0.33
0.50
0.74
1.00
0.15
Mental Health
NA
0.07
0.12
0.48
0.03
NA
0.11
0.22
0.29
0.43
Dual Eligible
NA
NA
NA
NA
0.61
NA
NA
NA
NA
0.32
Survey Year:
Case-Mix Adjuster
1
Model does not include MHP case-mixed adjuster.
2
The sample includes dually eligible beneficiaries, and the regression model includes an indicator for those cases.
The models corresponding to Table 6 were re-estimated, retaining regional interactions
for only GHP and age. Summaries of these new models appear as Table 7. After dropping MHP,
proxy, and education regional interactions, fairly consistent evidence of the heterogeneity of age
effects across regions emerged for 2000-2002 MFFS. 2003-2004 results are less consistent for
both GHP and age. As can be seen, there is a moderate amount of regional variation in the
30
magnitude of coefficients 2000-2004. On the other hand, regional patterns in these coefficients
are not very consistent in 2000-2004, raising questions about how to interpret these regional
interactions. The inconsistency of these findings from year to year in MFFS (including
inconsistency in which CMS regions have larger slopes from year to year) suggests that allowing
regional heterogeneity in CMA coefficients is probably not as helpful within MFFS or for
MFFS-vs.-MA CMA as it is within MA.
The existence of substantial linear interactions of case-mix adjusters with CMS Regions
within MA suggests that MFFS-vs.-MA CMA should employ these interaction terms in order to
ensure comparability. For Within-MFFS CMA, the existence of these interactions suggests
caution in comparing geo units from different CMS Regions. Future research should seek to
understand the instability over time of regional variation in CMA coefficients and should
consider eliminating these regional interactions for the sake of efficiency for Within-MFFS
CMA.
31
Table 7: Coefficients of Linear Interactions of Case-Mix Adjusters with CMS Regions, Excluding Dually Eligibles, Years 2000 –
2004.
Medicare
Survey
2000a 2001 2002 2003 2004b 2000a
Year:
P-value for
Partial F<.01 <.01 0.02 <.01 0.10
0.02
test for
GHP:
GHP INTERACTION
GHP-01 -0.15 -0.12 -0.15 -0.11 -0.12 -0.22
GHP-02 -0.17 -0.15 -0.11 -0.11 -0.09 -0.20
GHP-03 -0.16 -0.15 -0.12 -0.09 -0.14 -0.19
GHP-04 -0.12 -0.14 -0.10 -0.07 -0.09 -0.17
GHP-05 -0.15 -0.15 -0.15 -0.13 -0.13 -0.22
GHP-06 -0.11 -0.16 -0.11 -0.03 -0.11 -0.21
GHP-07 -0.13 -0.11 -0.14 -0.17 -0.09 -0.21
GHP-08 -0.19 -0.11 -0.19 -0.11 -0.12 -0.26
GHP-09 -0.21 -0.08 -0.14 -0.08 -0.11 -0.25
GHP-10 -0.08 -0.05 -0.09 -0.08 -0.18 -0.17
-0.15 -0.12 -0.13 -0.10 -0.12 -0.21
Average
AGE INTERACTION
P-value for
Partial F<.01 <.01 <.01 <.01 <.01 <.01
test for
AGE:
AGE-01 0.24 0.23 0.27 0.33 0.33 0.09
AGE-02 0.21 0.24 0.23 0.28 0.23 0.03
AGE-03 0.24 0.24 0.22 0.31 0.30 0.07
AGE-04 0.22 0.30 0.22 0.28 0.22 0.07
AGE-05 0.24 0.25 0.24 0.30 0.28 0.07
AGE-06 0.23 0.27 0.24 0.27 0.25 0.08
AGE-07 0.24 0.23 0.27 0.31 0.29 0.07
AGE-08 0.33 0.22 0.28 0.31 0.28 0.12
AGE-09 0.32 0.23 0.28 0.32 0.31 0.14
AGE-10 0.37 0.23 0.33 0.38 0.41 0.09
Average
0.26 0.24 0.26 0.31 0.29 0.08
a
Model does not include MHP case-mixed adjuster.
b
Health Care
Personal Dr
Specialist
2001
2002
2003
2004b 2000a 2001
2002
2003
2004b 2000a 2001
2002
2003
2004b
0.01
0.01
0.62
0.01
<.01
0.30
0.03
0.05
0.02
<.01
0.01
0.70
0.79
0.02
-0.15
-0.17
-0.18
-0.16
-0.15
-0.15
-0.15
-0.14
-0.11
-0.11
-0.15
-0.16
-0.17
-0.14
-0.14
-0.16
-0.15
-0.12
-0.23
-0.20
-0.16
-0.16
-0.15
-0.13
-0.14
-0.11
-0.14
-0.14
-0.14
-0.13
-0.14
-0.16
-0.14
-0.11
-0.13
-0.12
-0.13
-0.16
-0.12
-0.11
-0.16
-0.16
-0.20
-0.14
-0.14
-0.11
-0.12
-0.06
-0.09
-0.11
-0.12
-0.12
-0.16
-0.12
-0.12
-0.12
-0.12
-0.13
-0.12
-0.10
-0.11
-0.11
-0.07
-0.10
-0.11
-0.11
-0.08
-0.09
-0.05
-0.03
-0.07
-0.04
-0.07
-0.09
-0.05
-0.10
-0.07
-0.06
-0.02
-0.04
0.01
-0.04
-0.01
-0.05
-0.02
-0.02
-0.01
-0.03
-0.03
-0.05
-0.04
-0.03
-0.06
-0.01
-0.01
-0.01
-0.05
-0.09
-0.04
-0.11
-0.10
-0.17
-0.08
-0.13
-0.17
-0.17
-0.18
-0.18
-0.20
-0.15
-0.11
-0.17
-0.14
-0.14
-0.12
-0.13
-0.15
-0.12
-0.10
-0.04
-0.12
-0.09
-0.12
-0.12
-0.09
-0.12
-0.07
-0.08
-0.12
-0.11
-0.11
-0.10
-0.09
-0.07
-0.06
-0.04
-0.07
-0.05
-0.06
-0.07
-0.07
-0.09
-0.07
-0.05
-0.04
-0.07
-0.03
-0.08
-0.04
-0.04
-0.12
-0.07
-0.13
-0.07
<.01
<.01
0.01
<.01
0.01
0.01
<.01
0.14
0.06
0.04
0.04
0.01
0.21
0.06
0.05
0.08
0.07
0.09
0.05
0.08
0.03
0.01
0.02
0.03
0.06
0.03
0.05
0.05
0.05
0.09
0.06
0.12
0.07
0.09
0.07
0.04
0.07
0.07
0.05
0.08
0.07
0.06
0.09
0.11
0.09
0.02
0.04
0.06
0.04
0.07
0.08
0.06
0.10
0.06
0.03
0.09
0.08
0.14
0.09
0.12
0.08
0.07
0.09
0.08
0.04
0.01
0.01
0.02
0.02
0.05
0.06
0.06
0.05
0.06
0.03
0.04
0.04
0.04
0.03
0.05
0.07
0.06
0.06
0.07
0.05
0.06
0.04
0.11
0.03
0.12
0.11
0.00
0.03
-0.01
0.04
0.02
0.01
0.03
0.01
0.08
0.03
0.08
0.02
0.03
0.02
0.03
0.02
0.04
0.01
0.04
0.03
0.07
0.06
0.05
0.07
0.07
0.06
0.09
0.04
0.05
0.05
0.03
0.03
0.02
0.03
0.03
0.05
0.07
0.06
0.05
0.04
0.05
0.01
0.04
0.05
0.01
0.10
0.05
0.08
0.08
0.05
0.05
0.08
0.06
0.06
0.06
0.07
0.09
0.08
0.12
0.12
0.12
0.09
0.05
0.05
0.04
0.04
0.08
0.03
0.05
0.05
0.05
0.07
0.04
0.04
0.10
0.05
0.06
Sample includes dually eligible cases, and the regression models include an indicator for dually eligible beneficiaries.
32
SELECTING VARIABLES FOR THE CASE-MIX MODEL
Building on the findings and recommendations of the MA CMA Report and the MFFS
Pilot Test CMA Report, four case-mix models (differing in their sets of case-mix
adjusters/independent variables) were evaluated in the 2000 (Year 1) MFFS CMA Report. Two
of these models, plus two new models, were evaluated using 2001 (Year 2) data. In 2002 and
2003, MHP was assumed part of the base model. Four and three additional models were
assessed in 2002 and 2003, respectively. Finally, in 2004 the same three models used in 2003
are repeated and one new model adding dual eligibility indicator has been added.
Models Compared
In the 2000 Report, the first model evaluated was the base model for 1997-1999 MA:
age, general health perception, education, and proxy status, all coded categorically. The second
model evaluated was the model recommended by the MFFS Pilot Test CMA Report: the base
model plus the single-item mental health perception. The third model evaluated was the base
model plus the SF-12 mental health composite score. The fourth model evaluated was the base
model plus the SF-12 physical composite score.21
Using 2001 data, we evaluated four models: the first two models described above plus
two new models. One adds an interaction between linearly coded GHP and an indicator of age
under 65 (disabled). This allows GHP to have different meaning for disabled beneficiaries. The
analysis that supported the development of this model appears as Appendix C. The last model
adds to the base model a subdivision of under-65 age category into three parts (18-39, 40-54, 5564), and forces a linear pattern among those three subgroups, based on analyses described in
Appendix C.
The 2002-2003 base models include MHP. In 2002-2003, we compare the base model to
three alternative models: the first one added the consumer life satisfaction measure (CLS) to the
base model. The second and third models include the SF-12 mental health and SF-12 physical
composite scores calculated the same was as in the analysis of 2000 data. In 2002, we also
evaluated a fourth model, which added information regarding mode of administration.22
In 2004 the three models of 2003 were compared to the base model that included MHP.
An additional model that included an indicator for dual eligibility was also compared to the base
model. The analysis sample in 2004 included all the dual eligible beneficiaries.
21
The addition of a dual eligibility flag for Within-MFFS CMA will be considered, at least implicitly, within each of these four
models.
22
Because mode for those who self-selected to call confounds pure response bias mode effects (the effects of the same people
responding differently in different modes) with selection/composition effects (different people responding), we estimated
coefficients and the change in R-squared only on those whose follow-up was randomly assigned. Because the pure mode
effects should occur in all who responded by phone, we then projected those estimates (and calculated unit-level variance in
mode) for all who responded by mode.
33
Explanatory Power of Case-Mix Adjusters
Tables E2a and E2b in Appendix E summarize the explanatory power of the case-mix
adjusters involved in the four models that were compared in 2000 and 2001 using the four global
ratings.23 Tables 8a and 8b make comparisons for 2002-2004 data for the models described
above. The variables constituting the base model are labeled Group 1 and appear in Tables E2a
and 8a; the variables added to the base model to create the other models are labeled Group 2 and
appear in Tables E2b and 8b. Explanatory power was calculated in a different manner for Group
1 and Group 2 variables. The columns labeled ‘Change in R-square’ in these four tables report
the increase in R-square for the individual-level regression when adding the case-mix adjuster in
question to the base model (for Group 2 CMAs) or the base model without the case-mix adjuster
in question (for Group 1 CMAs). In other words, these columns report the marginal contribution
of each Group 1 CMA to the base model, controlling for other Group 1 CMAs, but reports the
additional contribution of each Group 2 CMA to the base model. The next two columns of these
Tables report the ratio of geo unit variance to error variance. The last two columns report the
(rescaled) explanatory power statistic. It should be noted that the middle two columns and hence
explanatory power vary with the choice of reporting entity.
2000-2001
Among Group 1 (base model) CMAs, education and general health perception were the
most important case-mix adjusters in both 2000 and 2001. Education’s explanatory power was
partially a function of its substantial variation by geo unit. Education and age have substantial
explanatory power for ratings of Medicare; general health perception and education has
substantial explanatory power for ratings of health care. In 2001, general health perception had
substantial explanatory power for ratings of specialists, as did education for ratings of personal
doctors. In general, the explanatory power of education and GHP in the base models was higher
in 2001 than 2000, a change which is primarily attributable to larger coefficients/larger changes
in R2 for these terms in the 2001 base model.
Among the Group 2 CMAs examined in Table E2b (2000 data), the SF-12 physical
health composite added virtually nothing to the R-square of the base model and therefore added
very little explanatory power. Both the mental health perception item and the SF-12 mental
health composite added substantial explanatory power to the base model for ratings of health
care and specialists. The contributions of the SF-12 mental health composite were somewhat
larger than for the single-item mental health perception. Given the small contribution of the SF12 physical health composite, this term was neither recommended in the 2000 Report nor
considered in 2001 comparisons. While the SF-12 mental health composite had somewhat
greater explanatory power than the MHP item, the former required 12 items on the instrument to
the latter’s one. For these reasons, the MHP item was recommended for 2001 use (and was added
to the corresponding MA instrument), whereas the SF-12 mental health composite was not (and
23
We follow MA practice in basing model comparisons on the four global ratings, rather than on report items or composites.
Because case-mix adjustment of composites occurs at the level of the report item, direct CMA models for composites are not
possible in general. Because the report items tend to show less variance than the global ratings (typically about 80% of
responses in the top category), these items are less powerful for comparisons of CMA models than are global ratings. The
appendices, which provide coefficients for all rating and report items, suggest that CMA effects tend to be fairly consistent for
global ratings and report items, a finding which has generally held throughout previous CAHPS CMA research.
34
questions exclusively serving the SF-12 were not added to the MA instrument). Had the MHP
item been used in 2000 CMA it would have been approximately as important an adjuster as GHP
and education within MFFS, and more important than age or proxy status.
Among the Group 2 CMAs examined in Table E2b (2001), the MHP item was easily the
most important. Its effects were very similar to those observed in 2000, having an impact
roughly comparable to GHP and education and larger than that of age or proxy status. The
contributions of the two terms involving beneficiaries under 65 were small, considerably less
than the contribution of age. These small impacts can be attributed to both the low frequency of
these beneficiaries when the dually eligible are excluded and the small variation in their
characteristics across geo-units. These factors might become important however in reporting
that focuses entirely on beneficiaries under the age of 65.
2002-2004
The addition of MHP to the base model in 2002-2004 affects the interpretation of the
GHP variable, with which it is highly correlated. Since the change in R-square reflects the
unique contribution of the variables, the drop in the E.P. for GHP in 2002 does not reflect a
decline in its importance, but rather the addition of MHP to the base model in 2002-2004. In that
light, the 2002-2004 results are consistent with 2000-2001 results. Note, for example, that the
GHP and MHP effects as Group 1 variables in 2002-2004 are comparable in magnitude to the
effects of MHP as a Group 2 variable in 2000-2001, a comparison which involves controlling for
the same other predictors. Although age is very important for predicting the rating of Medicare
2002-2004, the most important CMA variables in the 2002-2004 base models were education
and MHP. MHP had greater explanatory power in 2003 and 2004 than in 2002 for three of the
four global ratings.
Table 8a: Explanatory Power of Group 1 (Base Model) Case-Mix Adjusters, Geo Unit
Reporting Entities, Years 2002 – 2004
Case-Mix
Adjusters
Change in R-square
Survey Year: 2002a
Var(Geo Unit)
/Var(Error)
E.P.*1000
2003 b
2004c
2002a
2003 b
2004c
2002a
2003 b
2004c
0.0329
0.0028
0.0091
0.0061
0.0024
0.0001
0.0437
0.0015
0.0075
0.0050
0.0025
0.0000
0.0316
0.0016
0.0089
0.0033
0.0016
0.0000
0.0133
0.0207
0.0570
0.0160
0.0108
0.0043
0.0130
0.0219
0.0533
0.0169
0.0084
0.0041
0.0125
0.0246
0.0564
0.0203
0.0176
0.0046
0.4367
0.0571
0.5171
0.0980
0.0258
0.0003
0.5702
0.0328
0.4006
0.0851
0.0212
0.0000
0.3954
0.0401
0.5043
0.0681
0.0281
0.0000
0.0030
0.0041
0.0055
0.0133
0.0130
0.0125
0.0404
0.0532
0.0692
Medicare
AGE
GHP
EDUC
MHP
PROXY
ANSPROXY
Health Care
AGE
35
GHP
EDUC
MHP
PROXY
ANSPROXY
0.0064
0.0070
0.0107
0.0006
0.0002
0.0061
0.0057
0.0166
0.0006
0.0001
0.0066
0.0049
0.0126
0.0010
0.0000
0.0207
0.0570
0.0160
0.0108
0.0043
0.0219
0.0533
0.0169
0.0084
0.0041
0.0246
0.0564
0.0203
0.0176
0.0046
0.1328
0.3960
0.1715
0.0062
0.0007
0.1342
0.3042
0.2801
0.0052
0.0002
0.1615
0.2751
0.2554
0.0182
0.0001
0.0006
0.0024
0.0033
0.0081
0.0001
0.0000
0.0008
0.0011
0.0029
0.0135
0.0001
0.0000
0.0024
0.0010
0.0029
0.0120
0.0005
0.0001
0.0133
0.0207
0.0570
0.0160
0.0108
0.0043
0.0130
0.0219
0.0533
0.0169
0.0084
0.0041
0.0125
0.0246
0.0564
0.0203
0.0176
0.0046
0.0077
0.0490
0.1862
0.1292
0.0011
0.0001
0.0103
0.0232
0.1557
0.2274
0.0008
0.0002
0.0301
0.0240
0.1611
0.2439
0.0091
0.0002
0.0018
0.0002
0.0046
0.0093
0.0002
0.0001
0.0009
0.0004
0.0056
0.0070
0.0002
0.0003
0.0133
0.0207
0.0570
0.0160
0.0108
0.0043
0.0130
0.0219
0.0533
0.0169
0.0084
0.0041
0.0125
0.0246
0.0564
0.0203
0.0176
0.0046
0.0101
0.0187
0.2438
0.0887
0.0014
0.0017
0.0241
0.0040
0.2433
0.1572
0.0014
0.0005
0.0112
0.0096
0.3135
0.1425
0.0035
0.0015
Specialist
AGE
GHP
EDUC
MHP
PROXY
ANSPROXY
Personal Doctor
AGE
GHP
EDUC
MHP
PROXY
ANSPROXY
0.0008
0.0009
0.0043
0.0055
0.0001
0.0004
a
Sample of 43 states common to MA and MFFS; excluding dually eligible beneficiaries.
Sample of 42 states common to MA and MFFS; excluding dually eligible beneficiaries.
c
Sample of 41 states common to MA and MFFS; including dually eligible beneficiaries.
b
Among the Group 2 CMAs examined in Table 8b (2002-2004 data), the SF-12 physical
health composite added virtually nothing to the R-square of the base model and therefore added
very little explanatory power, as was the case in previous years. In general, the SF-12 mental
health composite added little explanatory power to a base model that already contains the MHP
item with the exception of a moderate contribution to the 2004 Health Care rating.
The Current Life Satisfaction (CLS) item added a moderate amount of explanatory power
to the base model. In 2002, its unique contributions are roughly equal to unique contributions of
GHP in the current model (less than age, education, and MHP; more than proxy status). In 2003
and 2004, CLS was more important than GHP for all four global ratings and more important than
age for three of four global ratings.24 On the other hand, CLS is less important than education
and does not add as much to the model as the one variable that has been added since 2000
(MHP). Dual eligibility is the among the three most important case-mix adjusters for the rating
of Medicare, but makes trivial contributions to the case-mix adjustment of the other three ratings.
An additional 2002 model added phone mode to the base model. Phone mode of
response, while varying little from geo-unit to geo-unit, has such a large unique contribution to
R-squared that it has consistently substantial explanatory power. If added to the case-mix model,
it would add at least as much as MHP added and has the potential to equal education as the most
24
Considering that E.P.s are inherently smaller in the Group 2 comparison than they would have been in the Group 1
comparison.
36
important case-mix adjustor. As noted in Appendix F, there are special concerns with the
implementation of adjustments based on mode of response.
Table 8b: Explanatory Power of Group 2 (Prospective) Case-Mix Adjusters, Geo Unit Reporting Entities,
Years 2002 – 2004
Change in
Case-Mix
Adjusters
Var(Geo Unit)
/Var(Error)
R-square
Survey Year: 2002a
E.P.*1000
2003 b
2004c
2002a
2003 b
2004c
2002a
2003 b
2004c
0.0044
0.0000
0.0032
0.0434
NA
0.0036
0.0002
0.0017
NA
NA
0.0052
0.0001
0.0019
NA
0.0088
0.0177
0.0183
0.0110
0.0071
NA
0.0138
0.0170
0.0107
NA
NA
0.0182
0.0201
0.0184
NA
0.0423
0.0783
0.0002
0.0353
0.3078
NA
0.0497
0.0031
0.0182
NA
NA
0.0939
0.0021
0.0340
NA
0.3714
0.0051
0.0003
0.0074
0.0397
NA
0.0100
0.0003
0.0085
NA
NA
0.0100
0.0005
0.0098
NA
0.0000
0.0177
0.0183
0.0110
0.0071
NA
0.0138
0.0170
0.0107
NA
NA
0.0182
0.0201
0.0184
NA
0.0423
0.0900
0.0049
0.0816
0.2812
NA
0.1383
0.0044
0.0915
NA
NA
0.1815
0.0110
0.1796
NA
0.0017
0.0023
0.0000
0.0039
0.0660
NA
0.0047
0.0000
0.0046
NA
NA
0.0054
0.0002
0.0035
NA
0.0001
0.0177
0.0183
0.0110
0.0071
NA
0.0138
0.0170
0.0107
NA
NA
0.0182
0.0201
0.0184
NA
0.0423
0.0398
0.0001
0.0430
0.4676
NA
0.0642
0.0005
0.0491
NA
NA
0.0980
0.0037
0.0646
NA
0.0025
0.0044
0.0001
0.0010
NA
NA
0.0047
0.0000
0.0009
NA
0.0003
0.0177
0.0183
0.0110
0.0071
NA
0.0138
0.0170
0.0107
NA
NA
0.0182
0.0201
0.0184
NA
0.0423
0.0440
0.0026
0.0139
0.2909
NA
0.0605
0.0011
0.0105
NA
NA
0.0847
0.0008
0.0160
NA
0.0145
Medicare
CLS
RPCS12
RMCS12
PHONE
Dual Eligible
Health Care
CLS
RPCS12
RMCS12
PHONE
Dual Eligible
Specialist
CLS
RPCS12
RMCS12
PHONE
Dual Eligible
Personal Doctor
CLS
RPCS12
RMCS12
PHONE
Dual Eligible
0.0025
0.0001
0.0013
0.0411
NA
a
Sample of 43 states common to MA and MFFS; excluding dually eligible beneficiaries.
Sample of 42 states common to MA and MFFS; excluding dually eligible beneficiaries.
c
Sample of 41 states common to MA and MFFS; including dually eligible beneficiaries.
b
37
Precision of Case-Mix Adjuster Estimates
Tables A1a, A1b, A1c, A3b, A3c, A3d, A2a, A2b, A2c, A2d and A2e in
Appendix A contain coefficients and standard errors for the base model and the
variation of the base model that adds MHP for all global ratings and report items.
Tables A4c and A4d additionally add CLS to 2002-2003 year models. Table A5e is
similar to Tables A4c and A4d, but adds dually eligible beneficiaries and a
corresponding indicator. Table 9 below outlines the differences among these appendix
tables. All 60 possible combinations of model, data, outcome form, and year are not
reported, but the 24 reported sets of coefficients do allow a variety of comparisons. As
can be seen, virtually all dummies are statistically significant for the four global ratings,
with t-statistics (coefficients divided by standard errors) often exceeding ten, indicating
that these coefficients are very well estimated. The same is true to a lesser extent for
the coefficients of the report items.
Table 9: Characteristics of Appendix Tables Listing Model Coefficients
Base
Model
Base
Model +
MHP
Data
All States,
No Dually
Eligible
2000 Data
Table A1a
(continuous)
2001 Data
Table A1b
(continuous)
2002 Data
Table A1c
(continuous)
Table A1a_d
(dichotomous)
Table A1b_d
(dichotomous)
Table A3b
(continuous)
Table A1c_d
(dichotomous)
Table A3c
(continuous)
Table A3d
(continuous)
Table A3b_d
(dichotomous)
Table A2b
(continuous)
Table A3c_d
(dichotomous)
Table A2c
(continuous)
Table A3d_d
(dichotomous)
Table A2d
(continuous)
All States,
No Dually
Eligible
All States,
With Dually
Eligible
Table A2a
(continuous)
2003 Data
2004 Data
Table A2e
(continuous)
Table A2e_d
(dichotomous)
Base
Model +
MHP +
CLS
All States
No Dually
Eligible
Table A4c
(continuous)
Table A4d
(continuous)
Table A4c_d
(dichotomous)
Table A4d_d
(dichotomous)
All States
With Dually
Eligible
Table A5e
(continuous)
Table A5e_d
(dichotomous)
One can compare the impact of the MHP dummies, for example, by comparing
Table A1b with A3b, or by comparing Table A1c with A3c. In the first comparison,
the base model coefficients remain well estimated in the model with MHP, and
coefficients for the mental health perception item are also well estimated. As with
general perceived health, higher perceived mental health is associated with more
38
positive ratings and reports of care. The addition of the mental health perception item
to the base model has little effect on base model coefficients, with the exception that the
magnitudes of the coefficients of the general health perception item are diminished
(because of correlation between the two items). In the second comparison, the
coefficients for the ratings are well estimated even after the addition of MHP; however,
for the reports this is not always the case.
. Comparisons of Tables A3b with A2b, or A3c with A2c reveal that the
exclusion or inclusion of the dually eligible has only very small impacts on other casemix coefficients.
Robustness to Dichotomization of Outcomes in Reporting
Tables A1a_d, A1b_d, A1c_d, A3b_d, A3c_d, A3d_d, A2e_d, A4c_d, A4d_d,
and A5e_d in Appendix A are parallel versions of Tables Ala, A1b, A1c, A3b, A3c,
A3d, A2e, A4c, A4d, and A5e, respectively, for the four global ratings, with the
exception that the global ratings have been dichotomized in the manner in which they
are sometimes presented to consumers: 10 vs. 0-9. The A1 tables compare the base
model, the A2 (including the dually eligibles) and A3 (excluding the dually eligibles)
Tables compare the model with MHP, and A4 (including the dually eligibles) and A5
(excluding the dually eligibles) Tables compare the model with CLS. Ideally, the
effects of the base model and base model plus MHP would be similar for the two
presentations.
This report focuses on case-mix adjustment of the ratings and report items in
their continuous form in order to maximize statistical power. For presentational
simplicity, reports to consumers, such as those found on Medicare.gov, present the
proportion of “best possible” responses. This dichotomous cut-point was chosen to
maximize statistical power. Robustness of our case-mix models to this dichotomization
would ensure that there were no systematic differences in the more powerful models
being examined here and the ones used to adjust consumer reports.25
An examination of Table A1a_d reveals that a large majority of the coefficients
for the dichotomized ratings are statistically significant and well estimated. The
direction of age effects is similar to that observed in the standard model, although the
distinction between those under 65 and 65 to 69 may not be as pronounced. The
direction of education effects is similar to the standard model for three of four ratings,
although specialists appear to be more often rated 10 by the better educated. Welleducated health consumers are known to expend more effort in searching for health
information related to specific medical conditions (Spranca, Ringel, et. al. 2004).
25
Because the models used for consumer reports have dichotomous outcomes, they could be based on logistic regression. As it
turns out, the very large sample sizes result in virtually indistinguishable results when ordinary least squares (linear) regression
is used. This convergence occurs because the global ratings tend to have means near 50% and the composites are themselves
means of several items, both of which increase the convergence of the normal approximation to the binomial. Given the
similarity, OLS was chosen for convenience, in that it permits partitioning of variance, computation of explanatory power
statistics, simple interpretation of coefficients, and comparability to the continuous models described here.
39
Perhaps the educated have invested more effort in their searches for specialist and
therefore are more satisfied with their choices.
The direction of health effects is similar to the standard model for three of four
ratings. The distinctions among good, fair, and poor health status appear to be weaker
for the dichotomized ratings, suggesting that the impact of these health statuses on
ratings is generally within the 0-9 range. The distinctions among excellent, very good,
and good health may be relatively more important in this range. More broadly, use of
the 0-9 vs. 10 split may emphasize the experiences of healthy and young-elderly relative
to the experiences of less healthy and older beneficiaries. Once again, dichotomized
specialists ratings behaved somewhat differently than in the standard model, with those
in worse health more likely to rate their specialists 10.
When MHP is added, the impact of GHP becomes smaller in general and
reverses direction for the dichotomized global rating of Health Care in some cases. Part
of this may be attributable to the very strong relationship of mental health perception to
global ratings of 10.
Other ongoing research investigates dichotomous presentation of global ratings
and reports in a manner that focuses attention on poor experiences by dichotomizing
near the 15th percentile distributions. Early results suggest that the CMA for this
method is interpretable and generally similar to the current approach, the resulting
power to compare plans is reasonable, and the resultant information ranks plans fairly
differently than the current approach. In particular, this “problem-oriented”
dichotomization may emphasize characteristics such as the proportion of beneficiaries
in poor health and the proportion of beneficiaries under age 65, in that these
characteristics have stronger predictive associations with the proportion of “low” ratings
and reports than with the proportion of “high” ratings and reports. This approach also
provides a way of dealing with the reversals in the GHP coefficients observed under
standard dichotomization. A manuscript on this topic is expected to be submitted in
2005.
Stability of MFFS CMA Coefficients
Table E3 of Appendix E compares 2000-2002 CMA coefficients for the four
global ratings for MFFS data in the 43 or 44 states with MA, excluding the dually
eligible. Table 10 below compares CMA coefficients for 2000-2004 data. Table E3
uses the base model without MHP, and Table 10 includes MHP. In 2004, the dually
eligible beneficiaries and an indicator were included in analyses. Those coefficients
that differ significantly (p < 0.05) across the years by a one-way analysis of variance are
marked with an asterisk. Note that the change in age categories in 2001 and again in
2002 affects the comparison of age coefficients.
As can be seen in Table 10, 2000-2004 MFFS CMA coefficients are generally
similar across years. The coefficients for beneficiaries 80 and older are positive and
40
moderate to large. There may also be a trend for proxy effects to be diminishing,
particularly in those cases in which a proxy answers in place of the beneficiary. In other
words, the tendency for proxies to be more negative than self-report appears to be
weakening. Preliminary work with propensity score matching suggests that true proxy
effects may be even smaller than they appear, and that they are primarily attributable to
non-spouse proxies. From 2000-2002, the slope of self-rated physical health (GHP)
increased, with ratings becoming more responsive to health. In this regard, the MFFS
pattern began to more closely resemble the pattern in MA. 2003 and 2004 patterns for
GHP represent a partial retreat from this trend. In other words, the steepness of slopes
in 2003 and 2004 are greater than in 2000 but equal to or less than what was observed in
2002. MHP slopes have also changed a little over 2000-2004, with general (though not
entirely consistent) pattern being towards greater sensitivity of ratings to MHP.
41
Table 10: Comparison of 2000- 2004 MFFS CMA Coefficients for Base Model plus MHP, MA and
MFFS Common States, No Dual Eligibles, Geo Unit Dummies Included in the Models
Global Ratings:
Rate Doctor
Rate Specialist
Survey Year
Case-Mix
Adjusters
2000a 2001b 2002c 2003d 2004e
2000a 2001b 2002c 2003d 2004e
0.08
-0.28
-0.26
-0.55 *
-0.12
0.02
0.03
-0.06
0.06
0.07
-0.09
0.09
-0.11
-0.11
0.04
0.02
0.00
0.09
0.03
0.10
0.05
AGE
AGE44
AGE64
AGE4564
AGE6569
AGE7579
AGE80
AGE8084
AGE85
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.05
0.08
-0.04
0.13
*
-0.07
-0.07
-0.11
0.08
0.22
-0.08
0.10
0.14
-0.09
0.11
0.11
-0.08 *
0.09
0.11
0.11
0.16
0.13
0.16
0.19
0.14
0.14 *
0.09
0.11
-0.08
-0.23
-0.24
0.17
0.14
-0.13
-0.23
-0.26
0.10
0.15
-0.09
-0.19
-0.25
0.09
0.12
-0.11
-0.22
-0.26
0.12 *
0.16
-0.09
-0.24
-0.26
0.07
0.12
-0.11
-0.20
-0.23
0.08
0.14
-0.13
-0.18
-0.26
0.08
0.13
-0.10
-0.19
-0.22
-0.01
0.08
-0.12
-0.21
-0.25
0.06
0.09
-0.08
-0.18
-0.24
0.22
0.09
-0.02
0.01
0.24
0.09
-0.05
0.01
0.22
0.08
-0.09
-0.08
0.14
0.07
-0.02
-0.04
0.16 *
0.06
-0.04 *
-0.06 *
0.10
0.06
-0.05
-0.09
0.22
0.09
-0.11
-0.17
0.20
0.08
-0.15
-0.23
0.15
0.06
-0.07
-0.16
0.07 *
0.05
-0.08 *
-0.15 *
0.36
0.14
-0.10
-0.21
0.37
0.12
0.00
-0.22
0.35
0.12
-0.10
-0.30
0.43
0.18
-0.12
-0.21
0.40
0.16
-0.08
-0.14
0.39
0.18
-0.17
-0.32
0.46
0.18
-0.11
-0.39
0.40
0.15
-0.13
-0.40
0.48
0.22
-0.14
-0.39
0.47 *
0.18
-0.15
-0.27
-0.13
-0.20
-0.13
-0.20
-0.07
-0.16
-0.08
-0.10
-0.09
-0.15
-0.11
-0.23
-0.04
-0.09
-0.05
-0.04
-0.04
-0.05
-0.12
-0.07 *
NA
NA
NA
NA
0.07
NA
NA
NA
NA
-0.02
-0.14
0.08
0.13
-0.07
0.06
0.08
0.05 *
0.08
GHP
EXCEL
VERYGOOD
FAIR
POOR
MHP
EXCEL
VERYGOOD
FAIR
POOR
PROXY
PROXY
ANSPROXY
DUAL ELIGIBLE
INDICATOR
42
*
*
*
*
Global Ratings:
Survey Year
Case-Mix
Adjusters
Rate Health Care
Rate Medicare
2000a 2001b 2002c 2003d 2004e
2000a 2001b 2002c 2003d 2004e
-0.56
-1.41
-1.25
-0.27
0.22
-0.72
-0.31
0.25
-0.84
-0.45
0.33
-0.97 *
*
-0.63
-0.37 *
0.33 *
0.36
0.41
0.40
0.45
0.52
0.60
0.53 *
0.62 *
AGE
AGE44
AGE64
AGE4564
AGE6569
AGE7579
AGE80
AGE8084
AGE85
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
GHP
EXCEL
VERYGOOD
FAIR
POOR
MHP
EXCEL
VERYGOOD
FAIR
POOR
PROXY
PROXY
ANSPROXY
DUAL ELIGIBLE
INDICATOR
-0.18
-0.59
-0.62
-0.15
-0.84
-0.76
-0.10
0.06
-0.05
-0.07
0.08
-0.11
-0.10
0.09
-0.19
-0.10
0.06
0.06
0.07
0.11
0.13
0.12
0.13
0.10
0.14
0.07
0.09
-0.16
-0.28
-0.31
0.10
0.13
-0.20
-0.26
-0.36
0.07
0.13
-0.15
-0.23
-0.33
0.01
0.07
-0.17
-0.28
-0.32
0.05 *
0.11 *
-0.12 *
-0.23
-0.29
0.07
0.16
-0.26
-0.42
-0.55
0.05
0.12
-0.28
-0.42
-0.55
0.06
0.12
-0.25
-0.37
-0.53
0.09
0.15
-0.24
-0.37
-0.48
0.15
0.14
-0.19
-0.31
-0.43
0.31
0.13
-0.08
-0.15
0.32
0.17
-0.13
-0.22
0.31
0.13
-0.17
-0.31
0.30
0.14
-0.12
-0.29
0.28
0.14
-0.13 *
-0.30 *
0.22
0.07
-0.01
-0.07
0.19
0.11
-0.05
-0.13
0.20
0.08
-0.12
-0.29
0.17
0.11
-0.04
-0.19
0.26
0.13
-0.09 *
-0.22 *
0.45
0.21
-0.18
-0.33
0.43
0.15
-0.09
-0.32
0.40
0.16
-0.17
-0.40
0.47
0.22
-0.16
-0.40
0.40 *
0.17 *
-0.14 *
-0.32
0.32
0.17
-0.10
-0.21
0.30
0.11
-0.07
-0.37
0.34
0.17
-0.16
-0.52
0.33
0.14
-0.15
-0.28
0.33
0.14
-0.10 *
-0.26 *
-0.15
-0.17
-0.14
-0.12
-0.11
-0.10
-0.11
-0.06
-0.15
-0.04 *
-0.30
-0.15
-0.32
-0.17
-0.28
-0.06
-0.32
-0.03
-0.34
0.03 *
NA
NA
NA
NA
0.00
NA
NA
NA
NA
-0.12
0.07
0.11
a
Sample of 43 states b Sample of 44 states
c
Sample of 43 states d Sample of 42 states
e
Sample of 41 states; including dual eligible beneficiaries.
* p-val < 0.05
43
-0.30
0.19
0.33
0.68
*
*
*
*
Figures 1-4 display FFS CMA coefficients for the four major CMA variables (age,
education, GHP, and MHP, respectively) for the four global ratings Within each figure, the
horizontal axis represents values of the ordinal CMA variable and the vertical axis represents the
CMA coefficients, after standardizing each line to a value of 0 for the reference category of the
CMA variable. This standardization was intended to facilitate comparison of CMA slopes by
suppressing small variation in absolute levels. Note that the line lengths vary in the age graph
because of redefinition of categories over time. In general, the more closely the lines track on a
given graph, the more consistent CMA patterns have been over time. Consistent CMA patterns
could be interpreted as either evidence that the CMA variable is mainly capturing response
tendencies as intended, since one might posit that response tendencies related to demographic
characteristics are unlikely to truly vary from year-to-year (see Elliott, Swartz, et.al., 2001).
Alternatively, they could include a true subgroup difference that has been quite stable over time.
More variable annual patterns could be interpreted as suggesting that at least some of what is
being captured by the CMA variable is true variation in subgroup experience, since it seems
more likely that subgroup experiences would vary annually.
To summarize the figures (1) education and MHP are the most stable CMAs over time,
suggesting they may tap most purely into response tendency (or alternately that these subgroup
experiences are very stable over time), when compared to age and GHP. (2) CMA patterns are
notably less stable for the rating of Medicare than for the other 3 ratings. This fits into a pattern
in which MHP and education are the most stable CMA variables over delivery system (FFS vs.
MA) and geography (CMS region). Moreover these two variables are the most important CMA
variables. Similarly, the rating of Medicare is associated with the least stable CMA coefficients
in these other regards as well. This instability may indicate that the rating of Medicare is more of
a barometer of the current popularity of the Medicare program than a direct measure of health
care experiences.
44
Figure 1. Parameter estimates from Table 10 plotted against age, by global rating, years 2000-2004
45
Figure 2. Parameter estimates from Table 10 plotted against education, by global rating, years 2000-2004
46
Figure 3. Parameter estimates from Table 10 plotted against GHP, by global rating, years 2000-2004
47
Figure 4. Parameter estimates from Table 10 plotted against MHP, by global rating, years 2000-2004
48
Recommendations for Case-Mix Adjustments
Model 1, the base model, is reliable, parsimonious, and reasonably robust with respect to
dichotomization of the global ratings. Models 2 and 3, which add the SF-12 mental and physical
scores, respectively, probably add too little to the explanatory power of Model 1 to justify a
change.
Model 4, which adds the current life satisfaction (CLS) item, may be in more of a gray
zone. Its empirical contributions are moderate, neither so small as to be easily ignorable nor so
important as to be a mandatory inclusion. The CLS item differs from existing CMA variables in
that it is not a demographic marker (like age, education, or health status) that may function both
as a true basis for differential care and also as a proxy for response bias patterns. Instead, it was
specifically designed to be a more direct measure of response bias, with those who profess
greater life satisfaction being more likely to rate all things, including health care experiences,
more positively. The CLS item has strong correlations with GHP and MHP. On the positive
side, use of this variable within a CMA model might help distinguish differential treatment of
beneficiaries by health status from systematic response patterns associated with beneficiary
health status. On the other hand, some feel that the use of the CLS item could lead to confusion
and criticism from some interested parties. See Appendix D for a more complete discussion of
these issues.
Model 5, which adds a dual eligible indicator to the base model with MHP, is similar to
Model 1. Among the four global ratings, the dual eligible dummy is only important for the rating
of Medicare, but its inclusion does satisfy concerns of face validity, much as is the case for the
use of proxy status CMA variables.
For these reasons, we recommend Model 5 (age, education, GHP, MHP, dual eligibility
and proxy status as dummies) for both MFFS-vs.-MA CMA and within-MFFS CMA in 2003.
For the former, we recommend (1) regional interactions of linear age categories and GHP with
CMS regions; (2) independent estimation of CMA coefficients for MFFS and MA; (3)
adjustment to the midpoint of MFFS and MA population means; and (4) the use of 2004
geographic equivalence weights (GEW) detailed in Appendix B.
We recommend consideration of further mode experiments within both MFFS and MA to
explore the viability of phone mode as a potentially very important case-mix adjustor, if a fairly
challenging one to implement.
It could be argued that both age and overall self-rated health are CMA variables that have
been retained through historical precedence and are no longer as important as they once were,
given the addition of self-rated mental health to the CMA model. Given that these variables also
are much less stable over time, delivery system, and geography than self-rated mental health and
education, it could be argued that an appealing and more parsimonious CMA model might drop
overall self-rated health and age as adjustment factors. Doing so could have the appeal of better
distinguishing true differential experiences by age and health status from patterns of response
tendency.
49
IMPACT OF CASE-MIX ADJUSTMENT OF GEO UNITS WITHIN MFFS, USING
CONTINUOUS SCORING
Table 11 summarizes the impact of case-mix adjustment of MFFS geo units, as compared
to one another on the four global ratings, using continuous scoring. The mean adjustments of
geo units may appear to be very small, ranging from 0.017 to 0.045 points on a scale with a
theoretical 11-point range. This is a little deceptive, however, because small differences are
important on these highly skewed scales, with means near nine. Variation in unadjusted geo unit
means is also small, so that the standard deviations of these case-mix adjustments are 15 to 44
percent of the standard deviations of the unadjusted geo unit means. The largest case-mix
adjustments range from 0.055 to 0.280 points, 41 to 160 percent of the standard deviations of the
unadjusted geo unit means. The impact of Within-MFFS CMA is therefore moderate, but not
negligible. Among the ratings, adjustments are largest for the rating of Medicare and smallest for
the rating of Personal Doctor. The magnitude of these impacts has been similar from year to
year.
Table 11: 2000-2004 Impact of Within-MFFS CMA, Geo Unit Reporting Entities, Base Model +
MHP
Medicare
Health Care
a
2001
2002
2003
2004
b
a
2001
2002
2003
2004b
Survey Year:
Mean absolute
adjustment
2000
0.041
0.042
0.044
0.044
0.044
0.038
0.038
0.036
0.045
0.042
Largest adjustment
0.280
0.280
0.243
0.234
0.264
0.197
0.177
0.138
0.177
0.184
STD (adj)
0.052
0.054
0.056
0.055
0.055
0.046
0.047
0.045
0.055
0.052
STD (adj)/STD
(unadjusted geo
unit means)
0.293
0.278
0.306
0.237
0.234
0.374
0.367
0.375
0.437
0.433
b
a
2001
2002
2003
2004b
2000
Doctor
a
b
Specialist
a
2001
2002
2003
2004
Survey Year:
Mean absolute
adjustment
2000
0.018
0.017
0.017
0.019
0.018
0.025
0.031
0.029
0.030
0.033
Largest adjustment
0.112
0.079
0.065
0.082
0.055
0.141
0.135
0.108
0.118
0.140
STD (adj)
0.022
0.022
0.021
0.023
0.022
0.031
0.039
0.036
0.038
0.041
STD (adj)/STD
(unadjusted geo
unit means)
0.161
0.151
0.150
0.162
0.165
0.180
0.238
0.257
0.281
0.275
2000
Model excludes MHP.
Dually eligible beneficiaries and an indicator for them were included in analysis.
51
IMPACT OF CASE-MIX ADJUSTMENT OF STATES WITHIN MFFS, USING
PERCENTAGE SCORING
The following impact analyses examine the effect of case-mix adjustment on the
percentage of best possible responses within states for MFFS data for five measures reported on
medicare.gov: two global ratings (Medicare/Plan and Care Received) and three report
composites (Care Without Waits, Doctor Communication, and Getting Needed Care). These
analyses are based on the CAHPS Macro using the recommended CMA model (including MHP)
for all 50 states (plus the District of Columbia and Puerto Rico) and allow examination of the
impact of CMA on the measures as they are presented to consumers.
As can be seen in Table 12, the mean absolute adjustment among states in 2004 is 1734% as large as the average (unadjusted) state deviation from the national MFFS mean. Because
the states themselves do not vary much, this corresponds to an average adjustment of 0.5-0.8%.
The largest adjustments are 1.9% to 3.1%. The sizes of the adjustments were similar to what was
observed 2001-2003.
It should be noted that in general the impact of CMA and explanatory power of CMA
variables is somewhat smaller in Within-MFFS CMA than in Within-MA CMA because the geo
units and states in MFFS are inherently less distinct from one another and more internally
heterogeneous than the corresponding plans in MA, thus lessening the potential for adjustment
within MFFS.26.
26
The impact of case-mix adjustment is a function of two factors: 1) the size of the coefficients at the
individual level and 2) the extent to which the case-mix characteristics vary from reporting unit to reporting unit.
MA plans have some ability to differentiate themselves from one another in their beneficiary populations through
marketing or through the features or services they provide. These provide a bit of market segmentation across MA
plans beyond the variation from geography alone. On the other hand, MFFS really varies only by geography. MFFS
vs. MA CMA has relatively large variation in case-mix characteristics because the set of MA plans, which are
relatively distinctive, varies from state to state. There really isn’t a corresponding variation within MFFS, so that
within MFFS CMA corrects only for the relatively subtle geographic variation in CMA variables.
52
Table 12: 2001-2004 Impact of Within-MFFS CMA, State Reporting Entities, Base Model +
MHP, Percentage Scoring
Care
W/o Wait Composite
Doctor Communication
Composite
Getting Nee
Compo
Survey Year:
2001a
2002
2003
2004b
2001a
2002
2003
2004b
2001a
2002
(1) Mean absolute adjustment
(2) Largest absolute
adjustment
(3) State with largest
adjustment
(4) Mean absolute deviation of
states from National Mean,
unadjusted
(5) Mean absolute adjustment
as a percentage of state-to-state
variation in scores [(1)/(4)]
0.6%
0.6%
0.7%
0.6%
0.6%
0.6%
0.6%
0.5%
0.7%
0.7%
+3.5%
-2.9%
-3.1%
-2.6%
+1.8%
-1.5%
-2.0%
-1.9%
+3.5%
-2.8%
PR
PR
PR
PR
MS
UT
PR
PR
PR
PR
2.8%
2.5%
3.0%
3.0%
2.0%
1.8%
1.9%
1.8%
1.6%
2.2%
21%
24%
22%
21%
30%
30%
31%
30%
44%
30%
Medicare
Rating
Survey Year:
(1) Mean absolute adjustment
(2) Largest absolute
adjustment
(3) State with largest
adjustment
(4) Mean absolute deviation of
states from National Mean,
unadjusted
(5) Mean absolute adjustment
as a percentage of state-tostate variation in scores
[(1)/(4)]
a
b
Health Care
Rating
2001a
2002
2003
2004b
2001a
2002
2003
2004b
1.0%
0.9%
0.8%
0.9%
0.7%
0.9%
0.7%
-3.4%
+2.6%
1.0%
+3.1%
-3.1%
-2.6%
-2.4%
-2.5%
-2.4%
-3.1%
ND
ND
ND
AK
PR
ND
UT
PR
PR
4.6%
4.2%
4.5%
4.6%
2.9%
2.8%
2.7%
2.2%
22%
20%
22%
17%
31%
25%
33%
31%
Model excludes MHP
Model includes dual eligible indicator
53
IMPACT OF CASE-MIX ADJUSTMENT AND COMPARISON WEIGHTS
ON NATIONAL MFFS VS. MA COMPARISON
The following impact analyses examine the effect of case-mix adjustment on the national
MFFS vs. MA comparison of the percentage of best possible responses for the two global ratings
(Medicare/Plan and Care Received) and three report composites (Care Without Waits, Doctor
Communication, and Getting Needed Care) discussed in the previous section. These analyses
are based on the CAHPS Macro using the recommended CMA model (including MHP, adding
dual eligibility in 2004) for all states with MA.
Three versions were compared 2001-2004: unadjusted27 MFFS-MA differences, MFFSMA differences with comparison weights only, and MFFS-MA differences with comparison
weights and CMA. The effect of comparison weights alone was defined as the difference
between the second version and the first. The effect of CMA alone was defined as the difference
between the third version and the second. The combined effect of CMA and comparison weights
was defined as the difference between the third version and the first. In 2002-2004 we also
display raw estimates that omit design and non-response weights internal to MFFS.
As can be seen in Table 13, both comparison weights and case-mix adjustment adjusted
in favor of MA for all five measures 2001-2002. In 2003-2004, comparison weights had small
and mixed adjustments, but case-mix adjustment adjusted in favor of MFFS for all five
measures, with the exception of one with no difference in 2004. The total adjustment was 0.23.6% per measure in 2004, 0.1% to 1.9% per measure in 2003, 0.2% to 1.2% per measure in
2002, and 2.2% to 4.6% per measure. The 2001 and 2004 adjustments were large enough to
reverse the sign of the unadjusted difference in two instances each.
In 2004, comparison weights had mixed effects of no more than 0.3%, except for a 0.8%
effect in favor of MFFS in the case of the Medicare rating. CMA alone had no effect for one
measure and adjusted by 0.7-2.8% in favor of MFFS for the other four measures. These are much
like 2003 findings, in which comparison weights alone adjusted by no more than 0.2% in either
direction. In 2003, CMA alone adjusted by 0.3-2.1% in favor of MFFS. CMA accounted for
most of the total adjustment 2003-2004.
In 2002, comparison weights adjusted by 0.0-0.2% in favor of MA and CMA adjusted by
0.1-1.0% and accounted for half to all of the adjustment. In 2001, comparison weights alone
adjusted the measures by 1.4-2.7% in favor of MA; CMA alone adjusted the measures by 0.81.9% in favor of MA. For all measures, comparison weights resulted in more of the adjustment
than did case-mix adjustment, which was responsible for 33-45% of the total adjustment.
Examination of the raw estimates show that the MFFS design and non-response weights
adjust by 0.0-0.7%. In 2003-2004, these adjustments were mixed in direction. In 2002, all such
adjustments were in favor of MFFS, correcting for under-representation of beneficiaries with
more positive ratings in the raw MFFS data. In terms of national mean differences between
MFFS and MA, the MFFS non-response and design weights were more important than the
comparison weights, but less important than case-mix adjustment in 2002-2004.
27 “unadjusted” MFFS-MA differences do not involve geographic equivalence weights (comparison weights), but
do involve simple population weights.
55
Comparison weights have gone from moderate adjustments in favor of MA in 2001 to
very small adjustments 2002-2004. One interpretation is that MFFS sample was initially scarce
in the geographic regions that had the least positive Medicare experiences among those regions
with MA penetration. The shrinking effect of the comparison weights may be attributable to the
reallocation of MFFS sample into the counties with high MA penetration but low population that
were initially underrepresented, in the efforts to reduce the comparison weights design effect. In
other words, the geographic distribution of the MFFS sample is much better matched to MA in
2004 than it was in 2001.
Case-mix adjustment has gone from moderate adjustments in favor of MA in 2001 to
small adjustments in favor of MA in 2002 to moderate adjustments in favor of MFFS in 20032004. Adjustments favoring MA probably correspond to MA having a higher proportion of
certain types of negative responders: the young and the better educated. Adjustments favoring
MFFS probably correspond to MFFS having a higher proportion of a different class of negative
responders: the unhealthy. The shift from adjustments favoring MA to adjustments favoring
MFFS could mean that age and education selection into MA is becoming weaker, but health
selection is becoming stronger. Future research should investigate trends in MFFS vs. MA casemix demographics.
56
Table 13: 2001-2004 National Estimates of MFFS-MA difference, Base Model + MHP, Percentage Scoring, Unadjusted, Comparison
Weighted, and Comparison Weighted + Case-Mix Adjusted
Care
w/o Wait Composite
Survey Year:
Raw MFFS-MA Estimate
Unadjusted MFFS-MA estimate
MFFS-MA estimate, with
Comparison Weights only
MFFS-MA estimate, with
Comparison Weights and Casemix Adjustment
Proportion of adjustment
attributable to CMA28
Doctor Communication
Composite
2001a
2002b
2003c
2004d
2001a
2002b
2003c
2004d
2001a
2002b
2003c
2004d
N/A
+1.6%
+1.4%
+2.0%
+2.2%
+2.7%
+0.6%
+0.2%
N/A
0.0%
-0.2%
+0.4%
+0.7%
+1.0%
-0.7%
-0.6%
N/A
+8.0%
+6.2%
+6.4%
+6.3%
+6.3%
+4.7%
+4.0%
-1.1%
+1.8%
+2.7%
-0.1%
-1.7%
+0.4%
+1.2%
-0.5%
+6.4%
+6.2%
+6.1%
+3.8%
-3.0%
+0.8%
+3.4%
+0.6%
-3.1%
-0.1%
+2.4%
0.9%
+5.6%
+5.9%
+6.4%
+3.8%
41%
83%
100%
N/a
45%
100%
86%
93%
33%
60%
N/A
0%
Medicare
Rating
Survey Year:
Raw MFFS-MA Estimate
Unadjusted MFFS-MA estimate
MFFS-MA estimate, with
Comparison Weights only
MFFS-MA estimate, with
Comparison Weights and Casemix Adjustment
Proportion of adjustment
attributable to CMA29
Getting Needed Care
Composite
2001
a
2002
b
2003
Health Care Rating
c
2004
d
2001
a
2002
b
2003
c
a
2004
d
N/A
+3.7%
+3.3%
+3.7%
+1.8%
+1.6%
-1.6%
-0.6%
N/A
+1.5%
+1.5%
+2.1%
+3.0%
+3.0%
+1.3%
+1.5%
+2.3%
+3.6%
+1.8%
0.2%
-0.6%
+2.1%
+3.2%
+1.7%
+1.5%
+3.5%
+3.9%
+3.0%
-1.8%
+1.9%
+4.9%
+3.5%
36%
50%
91%
78%
36%
100%
89%
90%
57
Sample of 44 States; model excludes
MHP.
b
Sample of 43 States
c
Sample of 41 States
d
Model includes dual eligibility
IMPACT OF CASE-MIX ADJUSTMENT ON STATE-LEVEL MFFS VS. MA
COMPARISONS, USING PERCENTAGE SCORING
The following impact analyses examine the effect of case-mix adjustment on state-level
MFFS vs. MA comparisons of the percentage of best possible responses for the five measures
discussed in the previous section. These analyses are based on the CAHPS Macro using the
recommended CMA model (including MHP, adding dual eligibles in 2004) and allow
examination of the impact of CMA on the measures as they are presented to consumers. The
effect of CMA was defined as in the previous section. The final rows of each section of Table 14
compare the amount of CMA to the amount of variation in the unadjusted state level effects in
order to give a sense of scale to the CMA.30
Case-mix adjustment had an average within-state effect of 0.7-2.8% in 2004. These
adjustments are generally larger than in 2003 and are represent a substantial increase in impact
since 2001-2002 for three measures (Doctor Communication, Medicare Rating, and Health Care
Rating). These 2004 adjustments are 27-67% of the standard deviation of the state-to-state
variation in the MFFS-MA difference. The largest adjustments were 1.7-7.5%. The case-mix
adjustment effects were in favor of MFFS in almost all cases in 2003-2004. In 2004, there were
three measures (again Doctor Communication, Medicare Rating, and Health Care Rating) for
which all states were adjusted in favor of MFFS. In contrast, 2001-2002 adjustments were not
only smaller, but were in favor of MA more often than not.
The 2002-2004 increase in state-level CMA adjustments in favor of MFFS, reflected in
both consistency and magnitude, cannot easily be explained by a corresponding trend in the
explanatory power of the CMA model at the individual level. Rather, it suggests that within-state
selection on characteristics related to CMA models (health, age, education) is becoming stronger.
It is likely that the tendency of MA beneficiaries to be healthier than MFFS beneficiaries within
states has become stronger over 2002-2004, and the CMA model is making greater adjustments
in favor of MFFS to account for this trend. Future research should explore this hypothesis.
30 In particular, the denomination in the last row is the mean absolute deviation of state level MFFS-MA differences
from the national MFFS-MA difference. The numerator is the mean absolute CMA of these state level estimates.
59
Table 14: 2001-2004 Impact of CMA on State-Level MFFS-MA Difference, Base Model + MHP, Percentage Scoring
Care
w/o Wait Composite
Doctor Communication
Composite
Getting Needed Care
Composite
2001a
2002b
2003c
2004d
2001a
2002b
2003c
2004d
2001a
2002b
2003c
2004d
1.2%
0.6%
0.9%
1.2%
0.7%
0.5%
1.6%
1.9%
0.4%
0.5%
0.9%
0.7%
Mean adjustment, signed (in favor of)
1.2%
MA
0.8%
MFFS
1.2%
MFFS
0.5%
MA
0.2%
MA
1.6%
MFFS
1.9%
MFFS
0.1%
MA
0.7%
FFS
0.5%
MFFS
Largest adjustment in favor of MFFS
0.3%
WV
0.6%
MA
0.3%
GA,
NM
2.1%
LA
2.2%
LA
1.3%
WV
0.9%
CT
3.2%
NC
2.9%
RI
1.3%
WV
0.9%
RI
2.4%
HI
1.6%
TX
1.7%
MS
1.2%
MS
0.2%
ND
2.1%
HI
1.2%
HI
0.3%
MS
None
0.8%
IN
2.4%
MS
1.7%
MS
1.7%
MD
4.5%
3.9%
2.6%
Survey Year:
Mean absolute adjustment of
Difference
Largest adjustment in favor of MA
2.6%
ND
0.1%
MA
Mean Absolute Deviation of State MFFS-MA Difference from National MFFS-MA Difference, Unadjusted
4.2%
3.4%
3.6%
3.3%
3.2%
Medicare
Rating
Survey Year:
Mean absolute adjustment of
Difference
Mean adjustment, signed (in favor of)
Largest adjustment in favor of MA
2.9%
2.9%
Health Care Rating
2001a
2002b
2003c
2004do
2001a
2002b
2003c
2004d
0.8%
0.8%
1.9%
2.8%
0.8%
0.7%
2.0%
2.4%
0.3%
1.8%
FFS
5.6%
HI
2.8%
MFFS
7.5%
MD
0.1%
MA
2.3%
DC
0.4%
3.0%
WV
0.2%
MA
1.8%
NM
2.0%
FFS
4.1%
LA
2.4%
MFFS
4.5%
CT
2.8%
VA
2.7%
NH
1.3%
UT
None
2.0%
VA
0.7%
UT
None
MFFS
Largest adjustment in favor of MFFS
2.7%
MFFS
2.5%
CT
1.3%
NH,
SD
Mean Absolute Deviation of State MFFS-MA Difference from National MFFS-MA Difference,
Unadjusted
5.9%
7.3%
7.0%
6.0%
60
4.2%
3.6%
4.4%
4.3%
3.7%
a
b
Sample of 44 States; model excluded MHP.
Sample of 43 States
c
Sample of 41 States
d
Model includes dual eligibility
61
SUMMARY OF IMPACT OF CASE-MIX ADJUSTMENT
The average impact of CMA alone is moderate on between-state comparisons of MFFS,
within-state comparisons of MFFS with MA, and national comparisons of MFFS with MA. The
adjustments of within-state comparisons of MFFS with MA were larger in 2003-2004 than in
2001-2002. The largest adjustments for several states were quite substantial for both betweenstate comparisons of MFFS and within-state comparisons of MFFS with MA. The effect of
CMA has shifted from favoring MA over MFFS strongly in 2001 to favoring MA more mildly in
2002 to favoring MFFS in 2003-2004.
63
APPENDIX A: CASE-MIX ADJUSTMENT COEFFICIENTS
Notes: All R-squares for Appendix Tables include variance attributable to the reporting
entity intercept vector. Coefficients in Appendix Tables are followed by their standard errors in
parentheses. The coefficients for proxy status should be interpreted as follows: the coefficient
for those beneficiaries receiving no assistance is 0, the coefficient for those beneficiaries
receiving some help (but answering for themselves) is represented by “PROXY”, and the
coefficient for those beneficiaries for whom proxy answered is represented by the sum of the
“PROXY” coefficient and the “ANSPROXY” coefficient. In other words, the ANSPROXY
coefficient estimates the difference between two types of proxy assistance. All tables in
Appendix A include all states.
Table A1a: 2000 Case-Mix Coefficients, Base Model, No Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.04
Q7
Personal Dr
0.02
Q11
Specialist
R-SQUARE
0.06
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.86
-0.29
0.19
0.32
(0.03)
(0.02)
(0.02)
(0.02)
-0.26
-0.12
0.06
0.08
(0.02)
(0.02)
(0.02)
(0.02)
-0.01
-0.14
0.07
0.11
(0.02)
(0.02)
(0.02)
(0.02)
-0.13
-0.07
0.05
0.05
(0.03)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.05
0.14
-0.25
-0.39
-0.53
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.05
0.08
-0.14
-0.24
-0.27
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.06
0.10
-0.07
-0.20
-0.20
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.06
0.11
-0.10
-0.17
-0.20
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.34
0.14
-0.08
-0.19
(0.03)
(0.02)
(0.02)
(0.02)
0.49
0.22
-0.17
-0.33
(0.03)
(0.02)
(0.01)
(0.02)
0.38
0.16
-0.08
-0.10
(0.02)
(0.01)
(0.01)
(0.02)
0.27
0.14
-0.13
-0.25
(0.04)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.32 (0.02)
-0.28 (0.03)
-0.20 (0.02)
-0.28 (0.03)
65
0.03
-0.15 (0.02)
-0.31 (0.03)
-0.16 (0.03)
-0.31 (0.04)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
0.03
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
0.04
0.02
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.11
-0.01
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.00
0.00
-0.00
(0.01)
(0.00)
(0.00)
(0.00)
-0.12
-0.05
0.03
0.07
(0.01)
(0.01)
(0.01)
(0.01)
-0.08
-0.01
0.00
0.00
(0.00)
(0.00)
(0.00)
(0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.02
-0.00
-0.01
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.01
-0.01
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.03
0.02
-0.06
-0.06
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.01
-0.00
-0.00
-0.01
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.03
-0.05
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.04
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.05
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.00
-0.01
-0.04
(0.00)
(0.00)
(0.00)
(0.00)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.02 (0.01)
-0.01 (0.00)
0.00 (0.01)
-0.01 (0.01)
-0.02 (0.01)
-0.01 (0.00)
0.01 (0.01)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
0.03
Q16
Getting
regular health
care appt.
0.02
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.06
0.00
0.02
0.02
(0.01)
(0.01)
(0.01)
(0.01)
-0.08
-0.00
0.03
0.04
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.02
0.01
0.03
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
-0.01
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.00
0.02
-0.04
-0.07
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.01
-0.03
-0.02
-0.04
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
-0.02
0.01
-0.04
-0.08
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
0.01
-0.04
-0.08
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
66
0.06
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.16
0.08
-0.07
-0.09
PROXIES
PROXY
ANSPROXY
-0.05 (0.01)
-0.04 (0.02)
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.05
-0.07
-0.10
(0.02)
(0.01)
(0.01)
(0.01)
-0.02 (0.01)
-0.01 (0.02)
0.13
0.07
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
-0.05 (0.01)
-0.03 (0.01)
0.29
0.14
-0.11
-0.19
(0.02)
(0.01)
(0.01)
(0.01)
-0.04 (0.01)
-0.04 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.03
Q28
Provider show
respect
0.03
Q29
Provider spend
enough time
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.05
-0.02
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
0.00
-0.00
-0.00
-0.02
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.03
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.02
0.00
0.01
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.03
-0.06
-0.09
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.03
-0.02
-0.04
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.04
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.04
-0.05
-0.07
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.16
0.08
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.20
0.10
-0.09
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.18
0.09
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.23
0.11
-0.10
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.11 (0.01)
-0.05 (0.01)
-0.12 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
R-SQUARE
0.02
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.07
-0.01
0.01
0.03
Q25
Office staff
helpful
0.03
(0.01)
(0.00)
(0.00)
(0.00)
-0.09
-0.02
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
67
0.03
-0.01 (0.01)
-0.11 (0.01)
-0.01 (0.01)
-0.11 (0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.00
-0.02
-0.04
-0.05
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.00
0.02
-0.05
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.03
-0.03
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
0.13
0.06
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.04 (0.01)
-0.04 (0.01)
-0.08 (0.01)
CUSTOMER SERVICE, INFORMATION, AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
0.04
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.04
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.16
-0.06
-0.00
0.04
(0.03)
(0.02)
(0.02)
(0.02)
-0.15
-0.03
0.03
0.03
(0.02)
(0.01)
(0.01)
(0.01)
-0.13
-0.04
0.01
0.02
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.06
-0.04
-0.09
-0.14
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.07
-0.01
-0.03
-0.02
-0.10
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
-0.02
0.02
-0.04
-0.06
-0.12
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.02
-0.01
-0.12
(0.04)
(0.02)
(0.02)
(0.03)
0.07
0.03
-0.05
-0.09
(0.02)
(0.01)
(0.01)
(0.02)
0.08
0.04
-0.08
-0.13
(0.02)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.10 (0.02)
-0.02 (0.04)
-0.13 (0.02)
0.01 (0.03)
68
-0.09 (0.02)
0.06 (0.03)
SINGLE REPORT OUTCOMES
Q33
Getting
special
equipment
Q34
Getting home
health care
0.09
Q36
Getting
special
therapy
Q38
Getting
prescription
medicines
0.07
0.06
R-SQUARE
0.05
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.18
-0.04
0.02
0.02
(0.02)
(0.02)
(0.01)
(0.01)
-0.16
0.01
-0.00
0.01
(0.04)
(0.04)
(0.03)
(0.03)
-0.17
-0.04
0.02
0.04
(0.02)
(0.02)
(0.02)
(0.02)
-0.21
-0.03
0.02
0.04
(0.01)
(0.00)
(0.00)
(0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.01
-0.04
-0.03
-0.06
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.04
-0.02
-0.08
0.01
-0.11
(0.03)
(0.03)
(0.03)
(0.04)
(0.03)
0.01
-0.00
-0.06
-0.05
-0.11
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.04
-0.02
-0.02
-0.02
-0.06
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.01
0.02
-0.03
-0.09
(0.04)
(0.02)
(0.01)
(0.01)
0.01
0.02
-0.09
-0.21
(0.08)
(0.04)
(0.02)
(0.03)
0.06
0.04
-0.05
-0.17
(0.04)
(0.02)
(0.01)
(0.02)
0.05
0.04
-0.06
-0.16
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
0.01 (0.02)
-0.08 (0.02)
-0.04 (0.03)
-0.06 (0.02)
-0.02 (0.02)
-0.02 (0.01)
0.02 (0.01)
SINGLE REPORT OUTCOMES
Q39
How often get
prescription
medicine
Q47
Getting good
quality
medical care
Q67
Providing
good quality
of life
0.04
0.04
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.16
-0.01
0.00
0.02
(0.01)
(0.00)
(0.00)
(0.00)
-0.22
-0.05
0.03
0.05
(0.01)
(0.01)
(0.01)
(0.01)
-0.23
-0.07
0.03
0.07
(0.01)
(0.01)
(0.01)
(0.01)
-0.86
-0.36
0.06
0.07
(0.06)
(0.06)
(0.06)
(0.06)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.03
-0.01
0.02
-0.00
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.04
0.00
-0.05
-0.07
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.00
0.03
-0.09
-0.14
-0.20
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
0.12
-0.15
-0.09
-0.29
(0.06)
(0.05)
(0.05)
(0.07)
(0.07)
GHP
EXCEL
0.03
Q48
Getting the
very best
care
0.01 (0.01)
0.14 (0.01)
69
0.21 (0.01)
-0.41 (0.20)
VERYGOOD
FAIR
POOR
0.02 (0.00)
-0.03 (0.00)
-0.07 (0.01)
0.07 (0.01)
-0.07 (0.01)
-0.11 (0.01)
0.09 (0.01)
-0.07 (0.01)
-0.11 (0.01)
-0.10 (0.09)
-0.11 (0.05)
-0.39 (0.05)
PROXIES
PROXY
ANSPROXY
0.00 (0.01)
0.01 (0.01)
-0.07 (0.01)
-0.07 (0.01)
-0.10 (0.01)
-0.11 (0.01)
-0.12 (0.04)
-0.20 (0.06)
70
Table A1a_d: 2000 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
Q46
Medicare
Q30
Health Care
0.01
Q7
Personal Dr
Q11
Specialist
0.02
0.02
R-SQUARE
0.06
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.13
-0.08
0.05
0.09
(0.01)
(0.00)
(0.00)
(0.00)
-0.02
-0.03
0.02
0.01
(0.01)
(0.00)
(0.00)
(0.00)
0.01
-0.04
0.03
0.04
(0.01)
(0.00)
(0.00)
(0.00)
-0.02
-0.03
0.00
-0.02
(0.01)
(0.00)
(0.00)
(0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.06
0.07
-0.08
-0.15
-0.19
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.01
0.02
-0.03
-0.07
-0.08
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.02
0.03
-0.03
-0.10
-0.11
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.04
-0.02
0.01
0.01
0.03
(0.00)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.13
0.03
-0.00
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
0.03
0.02
-0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
0.09
0.03
-0.01
0.01
(0.01)
(0.00)
(0.00)
(0.01)
-0.05
-0.02
0.03
0.07
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.08 (0.01)
-0.11 (0.01)
-0.02 (0.01)
-0.10 (0.01)
71
-0.03 (0.01)
-0.09 (0.01)
0.00 (0.00)
-0.05 (0.01)
Table A1b: 2001 MFFS Case-Mix Coefficients, Base Model, No Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
0.04
0.03
0.03
R-SQUARE
0.07
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.80
-0.27
0.21
0.34
0.39
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.21
-0.09
0.05
0.04
0.05
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.08
-0.10
0.07
0.09
0.10
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.13
-0.12
0.01
-0.01
-0.03
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.11
-0.27
-0.41
-0.53
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.07
0.12
-0.18
-0.24
-0.33
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.15
0.14
-0.12
-0.21
-0.24
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.06
0.12
-0.12
-0.17
-0.23
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.36
0.19
-0.11
-0.29
(0.02)
(0.01)
(0.02)
(0.02)
0.55
0.27
-0.21
-0.39
(0.02)
(0.01)
(0.01)
(0.02)
0.45
0.19
-0.09
-0.10
(0.02)
(0.01)
(0.01)
(0.02)
0.46
0.21
-0.20
-0.35
(0.04)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.32 (0.02)
-0.25 (0.03)
-0.15 (0.02)
-0.20 (0.03)
-0.13 (0.02)
-0.28 (0.03)
-0.07 (0.03)
-0.18 (0.04)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q22
Problem with
delays in
health care
0.03
0.02
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.09
-0.01
0.01
-0.01
-0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
-0.00
-0.01
-0.01
-0.00
(0.01)
(0.00)
(0.00)
(0.00)
(0.00)
-0.08
0.02
0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
-0.01
0.00
-0.00
0.00
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.02
-0.02
-0.01
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.01
-0.02
-0.03
-0.04
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
0.00
0.01
-0.05
-0.04
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.02
-0.01
-0.01
-0.00
-0.01
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
GHP
EXCEL
0.03
Q4
Problem
finding a
doctor/nurse
0.08 (0.01)
0.04 (0.01)
72
0.07 (0.01)
0.01 (0.00)
VERYGOOD
FAIR
POOR
0.03 (0.01)
-0.05 (0.01)
-0.15 (0.01)
0.03 (0.00)
-0.05 (0.00)
-0.14 (0.01)
0.04 (0.00)
-0.05 (0.00)
-0.13 (0.01)
0.01 (0.00)
-0.02 (0.00)
-0.04 (0.00)
PROXIES
PROXY
ANSPROXY
0.01 (0.01)
0.02 (0.01)
-0.00 (0.00)
0.02 (0.01)
0.01 (0.01)
-0.01 (0.01)
-0.01 (0.00)
0.02 (0.01)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
0.03
0.02
0.06
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.07
-0.00
0.01
-0.00
0.00
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.10
-0.02
-0.00
-0.02
-0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
0.01
0.01
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
0.01
0.01
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.01
0.03
-0.04
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.00
-0.04
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
0.01
-0.04
-0.07
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.02
-0.05
-0.04
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.19
0.10
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.14
0.06
-0.07
-0.12
(0.02)
(0.01)
(0.01)
(0.01)
0.14
0.08
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.28
0.14
-0.12
-0.20
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.05 (0.01)
0.01 (0.01)
-0.01 (0.02)
-0.03 (0.01)
-0.00 (0.01)
-0.01 (0.01)
-0.07 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.03
Q28
Provider show
respect
0.03
Q29
Provider spend
enough time
R-SQUARE
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.04
-0.01
0.01
0.00
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.00
-0.01
-0.04
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
0.01
0.01
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.01
0.00
-0.02
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.03
-0.07
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.02
-0.04
-0.03
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.05
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.04
-0.07
-0.08
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
73
0.03
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.18
0.09
-0.07
-0.12
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.08 (0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.21
0.10
-0.08
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
-0.05 (0.01)
-0.09 (0.01)
0.20
0.10
-0.08
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
-0.01 (0.01)
-0.08 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.02
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.07
-0.01
0.01
0.02
0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.06
-0.02
0.01
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.00
-0.03
-0.04
-0.05
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.00
0.02
-0.06
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.07
0.04
-0.03
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
0.15
0.08
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.05 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.04
0.05
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.11
-0.01
0.10
0.07
0.02
EDUCATION
LESS8GRD
SOMEHIGH
-0.07 (0.04)
0.00 (0.03)
(0.03)
(0.02)
(0.02)
(0.03)
(0.04)
-0.12
-0.03
0.04
0.02
0.06
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.09 (0.02)
-0.01 (0.01)
74
-0.13
-0.03
0.01
0.04
0.06
(0.02)
(0.02)
(0.02)
(0.02)
(0.03)
-0.04 (0.03)
-0.02 (0.02)
0.27
0.12
-0.08
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
-0.01 (0.01)
-0.08 (0.01)
SOMECOLL
COLLGRAD
COLLMORE
-0.09 (0.02)
-0.13 (0.03)
-0.20 (0.03)
-0.03 (0.01)
-0.05 (0.02)
-0.07 (0.02)
-0.06 (0.02)
-0.09 (0.02)
-0.14 (0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.02
-0.03
-0.15
0.07
0.04
-0.07
-0.16
0.07
0.07
-0.09
-0.17
PROXIES
PROXY
ANSPROXY
-0.10 (0.03)
0.06 (0.04)
(0.04)
(0.02)
(0.02)
(0.03)
(0.02)
(0.01)
(0.01)
(0.02)
-0.10 (0.02)
-0.02 (0.03)
(0.03)
(0.02)
(0.02)
(0.02)
-0.06 (0.02)
0.04 (0.03)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
R-SQUARE
0.05
0.11
0.06
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.19
-0.03
0.03
0.02
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
-0.24
-0.05
0.00
0.01
0.02
(0.04)
(0.04)
(0.03)
(0.03)
(0.03)
-0.17
-0.02
0.03
0.01
0.05
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
0.01
-0.05
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
0.02
-0.01
-0.12
-0.06
-0.11
(0.03)
(0.03)
(0.02)
(0.04)
(0.04)
-0.02
-0.02
-0.08
-0.05
-0.11
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.05
-0.01
-0.09
(0.03)
(0.02)
(0.01)
(0.01)
0.07
0.03
-0.11
-0.28
(0.07)
(0.03)
(0.02)
(0.03)
0.06
0.04
-0.06
-0.17
(0.03)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
0.02 (0.02)
-0.07 (0.02)
0.00 (0.03)
75
-0.04 (0.01)
0.00 (0.02)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.07
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.23
-0.02
0.02
0.04
0.05
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.20
-0.03
0.02
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.03
-0.02
-0.01
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.09
-0.04
0.01
0.03
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.07
0.04
-0.07
-0.16
(0.01)
(0.00)
(0.00)
(0.01)
-0.08
0.01
-0.03
-0.07
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.00 (0.00)
0.02 (0.01)
0.02 (0.01)
0.05 (0.01)
76
Table A1b_d: 2001 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.06
0.02
0.02
0.01
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.12
-0.08
0.05
0.09
0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.04
0.01
0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.04
0.02
0.02
0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.00
-0.03
0.01
-0.01
-0.04
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.06
0.07
-0.09
-0.15
-0.19
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.03
-0.04
-0.08
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
0.03
-0.04
-0.09
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.04
-0.01
0.02
0.02
0.01
(0.00)
(0.00)
(0.00)
(0.01)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.15
0.05
-0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.00
-0.00
(0.01)
(0.00)
(0.00)
(0.01)
0.11
0.04
-0.00
0.02
(0.01)
(0.00)
(0.00)
(0.01)
-0.03
-0.02
0.04
0.07
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.09 (0.01)
-0.09 (0.01)
-0.03 (0.01)
-0.07 (0.01)
77
-0.02 (0.01)
-0.06 (0.01)
0.02 (0.00)
-0.04 (0.01)
Table A1c: 2002 Case-Mix Coefficients, Base Model, No Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.05
0.03
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-1.47
-0.77
-0.31
0.24
0.40
0.44
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.62
-0.11
-0.07
0.07
0.11
0.11
(0.05)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
0.03
0.17
-0.08
0.09
0.16
0.11
(0.05)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.35
-0.03
-0.06
0.06
0.09
0.03
(0.06)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
0.10
-0.23
-0.36
-0.51
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.05
0.12
-0.13
-0.21
-0.31
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.09
0.14
-0.08
-0.18
-0.23
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.06
0.11
-0.08
-0.17
-0.20
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.40
0.19
-0.21
-0.52
(0.02)
(0.01)
(0.02)
(0.03)
0.55
0.25
-0.27
-0.51
(0.02)
(0.01)
(0.01)
(0.02)
0.43
0.17
-0.16
-0.22
(0.02)
(0.01)
(0.01)
(0.02)
0.44
0.19
-0.23
-0.41
(0.03)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.29 (0.02)
-0.13 (0.03)
-0.12 (0.02)
-0.15 (0.03)
-0.09 (0.02)
-0.20 (0.03)
-0.07 (0.02)
-0.10 (0.03)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
R-SQUARE
0.03
0.03
0.04
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.21
-0.08
-0.01
0.00
0.00
0.00
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.16
-0.08
-0.00
0.01
0.00
-0.00
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
78
-0.15
-0.07
0.02
0.01
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.37
-0.16
-0.02
0.01
0.01
0.04
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.01
-0.00
-0.00
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
-0.01
-0.00
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.01
-0.04
-0.02
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.01
0.01
-0.04
-0.06
-0.08
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.03
-0.06
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.02
-0.04
-0.14
(0.01)
(0.00)
(0.00)
(0.01)
0.08
0.04
-0.06
-0.15
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.05
-0.03
-0.15
(0.03)
(0.02)
(0.02)
(0.02)
PROXIES
PROXY
ANSPROXY
0.01 (0.01)
0.01 (0.01)
0.01 (0.01)
-0.00 (0.01)
-0.01 (0.01)
0.02 (0.01)
-0.01 (0.02)
-0.10 (0.03)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.04
0.04
0.04
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.20
-0.02
0.01
0.02
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.27
-0.08
-0.02
0.01
0.04
0.06
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.21
-0.03
0.00
0.03
0.05
0.07
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.08
0.01
0.00
0.02
0.03
0.03
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.00
0.03
-0.03
-0.03
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.02
-0.03
-0.00
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
0.01
0.03
-0.06
-0.09
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.05
-0.05
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.18
0.09
-0.10
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.15
0.08
-0.09
-0.16
(0.02)
(0.01)
(0.01)
(0.01)
0.22
0.11
-0.10
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
0.33
0.14
-0.10
-0.18
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
-0.01 (0.01)
-0.00 (0.01)
0.02 (0.02)
79
-0.02 (0.01)
-0.00 (0.01)
-0.11 (0.01)
0.04 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.03
Q29
Provider spend
enough time
R-SQUARE
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.15
-0.03
-0.00
0.02
0.03
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.10
0.04
0.02
0.00
-0.01
-0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.14
-0.01
0.00
0.02
0.04
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.14
0.01
-0.00
0.01
0.02
0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.04
-0.05
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.03
-0.02
-0.03
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.04
-0.04
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.06
-0.05
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.18
0.09
-0.09
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.21
0.11
-0.11
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.19
0.09
-0.09
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.27
0.13
-0.11
-0.19
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
-0.04 (0.01)
-0.06 (0.01)
-0.03 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.22
-0.06
-0.01
0.02
0.03
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.24
-0.05
-0.02
0.03
0.05
0.06
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.01
-0.03
-0.03
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.00
0.03
-0.04
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
80
0.04
-0.03 (0.01)
-0.03 (0.01)
-0.01 (0.01)
-0.02 (0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.07
0.03
-0.04
-0.07
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.01 (0.01)
(0.01)
(0.00)
(0.00)
(0.01)
0.15
0.07
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
-0.03 (0.01)
-0.03 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
0.06
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.17
-0.10
-0.04
0.02
0.04
0.07
(0.05)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.19
-0.10
-0.06
0.04
0.06
0.06
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.21
-0.14
-0.04
0.04
0.07
0.05
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.01
-0.02
-0.05
-0.10
-0.14
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.06
0.02
-0.02
-0.03
-0.10
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.06
0.02
-0.06
-0.05
-0.17
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.01
-0.07
-0.22
(0.03)
(0.02)
(0.02)
(0.03)
0.11
0.07
-0.08
-0.23
(0.02)
(0.01)
(0.02)
(0.02)
0.01
0.03
-0.07
-0.22
(0.03)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.05 (0.03)
-0.10 (0.04)
-0.13 (0.02)
-0.01 (0.03)
-0.13 (0.02)
0.01 (0.03)
SINGLE REPORT OUTCOMES
R-SQUARE
AGE
AGE44
AGE4564
AGE6569
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
0.06
0.12
0.07
-0.34 (0.03)
-0.18 (0.01)
-0.02 (0.01)
-0.37 (0.07)
-0.26 (0.03)
-0.03 (0.03)
81
-0.33 (0.03)
-0.20 (0.02)
-0.04 (0.01)
AGE7579
AGE8084
AGE85
0.01 (0.01)
0.04 (0.01)
0.06 (0.01)
0.03 (0.03)
0.05 (0.03)
0.06 (0.03)
0.01 (0.01)
0.02 (0.01)
0.04 (0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.02
-0.03
-0.04
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.01
0.05
-0.02
-0.03
-0.12
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.03
0.01
-0.04
-0.04
-0.11
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.04
-0.05
-0.13
(0.03)
(0.01)
(0.01)
(0.01)
0.03
0.05
-0.11
-0.28
(0.06)
(0.03)
(0.02)
(0.02)
0.02
0.04
-0.07
-0.17
(0.02)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
0.01 (0.01)
-0.07 (0.02)
-0.01 (0.03)
-0.03 (0.01)
0.01 (0.02)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.08
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.40
-0.23
-0.02
0.03
0.05
0.07
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.39
-0.19
-0.04
0.01
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.03
-0.03
-0.01
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.08
-0.04
0.01
0.05
0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.07
0.04
-0.08
-0.19
(0.01)
(0.00)
(0.00)
(0.01)
-0.07
-0.00
-0.04
-0.11
(0.01)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.00)
0.02 (0.01)
0.02 (0.01)
0.03 (0.01)
82
Table A1c_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model,
No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.02
0.02
0.01
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.17
-0.09
-0.07
0.06
0.11
0.12
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.11
0.00
-0.03
0.02
0.03
0.01
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.02
0.03
-0.03
0.03
0.04
0.03
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.04
0.02
-0.02
0.02
0.01
-0.03
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.05
0.07
-0.07
-0.15
-0.19
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.03
-0.03
-0.08
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.03
-0.08
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.04
-0.01
0.01
0.00
0.00
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.16
0.05
-0.03
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
0.08
0.04
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
0.12
0.04
-0.02
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
-0.00
-0.01
0.02
0.03
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.07 (0.01)
-0.05 (0.01)
-0.01 (0.01)
-0.07 (0.01)
83
0.00 (0.01)
-0.06 (0.01)
0.03 (0.00)
-0.05 (0.01)
Table A2a: 2000 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.06
0.06
0.03
0.04
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.69
-0.28
0.19
0.32
(0.02)
(0.02)
(0.02)
(0.02)
-0.22
-0.12
0.06
0.10
(0.02)
(0.02)
(0.02)
(0.02)
0.01
-0.13
0.07
0.11
(0.02)
(0.02)
(0.02)
(0.02)
-0.08
-0.07
0.07
0.08
(0.03)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.08
0.16
-0.27
-0.41
-0.56
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.10
0.11
-0.17
-0.28
-0.32
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.11
0.12
-0.08
-0.23
-0.24
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.09
0.11
-0.13
-0.21
-0.25
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.20
0.07
-0.02
-0.06
(0.03)
(0.02)
(0.02)
(0.02)
0.30
0.13
-0.08
-0.12
(0.03)
(0.02)
(0.01)
(0.02)
0.22
0.08
-0.01
0.02
(0.02)
(0.02)
(0.01)
(0.02)
0.12
0.05
-0.05
-0.07
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.15
-0.17
-0.24
-0.40
(0.02)
(0.02)
(0.02)
(0.03)
0.23
-0.21
-0.36
-0.56
(0.02)
(0.01)
(0.02)
(0.03)
0.21
-0.13
-0.21
-0.32
(0.02)
(0.01)
(0.02)
(0.03)
0.21
-0.18
-0.34
-0.49
(0.02)
(0.02)
(0.03)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.30 (0.02)
-0.25 (0.03)
-0.17 (0.02)
-0.24 (0.03)
-0.14 (0.02)
-0.29 (0.03)
-0.12 (0.02)
-0.27 (0.04)
DUAL ELIG
0.31 (0.02)
0.01 (0.02)
0.09 (0.02)
0.05 (0.03)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
R-SQUARE
0.04
Q21
Problem
getting
necessary care
0.04
Q4
Problem
finding a
doctor/nurse
0.05
84
Q22
Problem with
delays in
health care
0.03
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.07
-0.01
0.01
0.04
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.00
0.00
0.01
(0.01)
(0.00)
(0.00)
(0.00)
-0.11
-0.05
0.03
0.07
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
-0.01
0.00
0.01
(0.00)
(0.00)
(0.00)
(0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.01
-0.01
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
-0.01
-0.01
-0.02
-0.04
(0.00)
(0.00)
(0.00)
(0.01)
(0.01)
0.05
0.03
-0.07
-0.07
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
-0.00
-0.01
-0.00
-0.01
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.02
-0.02
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.01
-0.03
-0.09
(0.01)
(0.00)
(0.00)
(0.01)
0.04
0.02
-0.03
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
-0.00
-0.00
-0.01
-0.02
(0.01)
(0.00)
(0.00)
(0.00)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.04
-0.10
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.02
-0.03
-0.07
-0.14
(0.00)
(0.00)
(0.00)
(0.01)
0.03
-0.03
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.02)
0.01
-0.01
-0.02
-0.07
(0.00)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
0.05 (0.01)
-0.01 (0.00)
0.03 (0.01)
0.00 (0.01)
0.00 (0.01)
-0.01 (0.00)
0.02 (0.00)
DUAL ELIG
-0.10 (0.01)
-0.07 (0.00)
-0.02 (0.01)
-0.04 (0.00)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
R-SQUARE
0.04
0.04 0.03 0.06
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.05
0.00
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.00
0.03
0.06
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
-0.02
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
-0.01
0.01
0.03
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.01
0.02
-0.05
-0.08
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
0.02
-0.03
-0.03
-0.06
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
-0.01
0.02
-0.05
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
0.02
-0.04
-0.09
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
0.10 (0.01)
0.05 (0.01)
0.07 (0.02)
0.03 (0.01)
85
Q16
Getting
regular health
care appt.
0.07 (0.01)
0.04 (0.01)
Q23
Waiting 15
minutes past
appt.
0.23 (0.02)
0.11 (0.01)
FAIR
POOR
-0.04 (0.01)
-0.05 (0.01)
-0.03 (0.01)
-0.03 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.08 (0.01)
-0.13 (0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.06
-0.11
-0.13
0.07
-0.05
-0.13
-0.13
0.07
-0.06
-0.10
-0.10
0.06
-0.05
-0.11
-0.14
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
-0.03 (0.01)
-0.00 (0.01)
-0.02 (0.02)
-0.05 (0.01)
-0.01 (0.01)
-0.04 (0.01)
-0.02 (0.02)
DUAL ELIG
-0.03 (0.01)
-0.06 (0.01)
-0.03 (0.01)
0.01 (0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.04
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.04
-0.02
0.01
0.03
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.00
0.00
-0.01
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.03
0.01
0.03
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.02
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
0.04
-0.07
-0.09
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.03
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.04
-0.04
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.07
0.05
-0.06
-0.08
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.10
0.05
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.06
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.06
-0.03
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
0.14
0.07
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.06
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.10
-0.07
-0.13
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.06
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.11
-0.07
-0.13
-0.18
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
-0.09 (0.01)
-0.03 (0.01)
-0.10 (0.01)
0.01 (0.01)
-0.09 (0.01)
0.01 (0.01)
-0.09 (0.01)
DUAL ELIG
-0.01 (0.01)
0.02 (0.01)
0.01 (0.01)
0.01 (0.01)
86
0.04
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.05
-0.01
0.02
0.04
(0.01)
(0.00)
(0.00)
(0.00)
-0.07
-0.02
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.01
-0.02
-0.04
-0.06
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.01
0.03
-0.06
-0.09
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.02
-0.02
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.04
-0.03
-0.07
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.05
-0.11
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.02 (0.01)
-0.03 (0.01)
-0.07 (0.01)
DUAL ELIG
-0.04 (0.01)
-0.02 (0.01)
CUSTOMER SERVICE, INFORMATION, AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.05
0.05
0.04
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.12
-0.05
0.00
0.03
(0.03)
(0.02)
(0.02)
(0.02)
-0.14
-0.03
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
87
-0.10
-0.04
0.01
0.03
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.00
0.07
-0.05
-0.10
-0.15
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.07
-0.01
-0.03
-0.02
-0.12
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.02
0.03
-0.04
-0.06
-0.13
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.00
-0.00
0.00
-0.07
(0.04)
(0.02)
(0.02)
(0.03)
0.04
0.01
-0.02
-0.05
(0.02)
(0.01)
(0.01)
(0.02)
0.06
0.02
-0.04
-0.09
(0.03)
(0.02)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.04
-0.05
-0.14
(0.02)
(0.02)
(0.02)
(0.04)
0.04
-0.05
-0.11
-0.15
(0.01)
(0.01)
(0.02)
(0.02)
0.03
-0.03
-0.12
-0.14
(0.02)
(0.01)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.09 (0.02)
0.00 (0.04)
-0.12 (0.01)
0.02 (0.02)
-0.09 (0.02)
0.09 (0.02)
DUAL ELIG
-0.03 (0.03)
0.03 (0.02)
0.03 (0.02)
SINGLE REPORT OUTCOMES
Q33
Getting
special
equipment
Q34
Getting home
health care
0.08
Q36
Getting
special
therapy
0.08
Q38
Getting
prescription
medicines
R-SQUARE
0.06
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.16
-0.04
0.02
0.03
(0.02)
(0.02)
(0.01)
(0.01)
-0.11
0.04
0.02
0.03
(0.03)
(0.03)
(0.03)
(0.02)
-0.15
-0.03
0.02
0.04
(0.02)
(0.02)
(0.02)
(0.02)
-0.19
-0.03
0.02
0.05
(0.01)
(0.00)
(0.00)
(0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.00
0.00
-0.05
-0.04
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.03
0.00
-0.09
0.00
-0.12
(0.02)
(0.02)
(0.02)
(0.03)
(0.03)
0.02
0.01
-0.06
-0.07
-0.12
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.03
-0.01
-0.03
-0.03
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.00
0.02
-0.01
-0.06
(0.04)
(0.02)
(0.01)
(0.01)
0.02
0.02
-0.07
-0.14
(0.07)
(0.03)
(0.02)
(0.02)
0.06
0.02
-0.03
-0.13
(0.04)
(0.02)
(0.01)
(0.02)
0.04
0.03
-0.05
-0.13
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
0.03 (0.02)
-0.02 (0.01)
0.02 (0.03)
-0.04 (0.02)
88
0.06
-0.01 (0.02)
-0.04 (0.02)
0.02 (0.00)
-0.03 (0.00)
MHFAIR
MHPOOR
-0.03 (0.01)
-0.10 (0.02)
-0.08 (0.02)
-0.17 (0.03)
-0.08 (0.02)
-0.16 (0.02)
-0.06 (0.01)
-0.09 (0.01)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.03 (0.02)
-0.04 (0.02)
-0.03 (0.02)
-0.05 (0.02)
-0.00 (0.02)
-0.01 (0.01)
0.04 (0.01)
DUAL ELIG
-0.05 (0.01)
-0.01 (0.02)
-0.06 (0.02)
-0.02 (0.01)
SINGLE REPORT OUTCOMES
Q39
How often get
prescription
medicine
Q47
Getting good
quality
medical care
Q48
Getting the
very best
care
Q67
Providing
good quality
of life
R-SQUARE
0.04
0.04
0.05
0.04
AGE
AGE64
AGE6569
AGE7579
AGE80
-0.14
-0.02
0.01
0.03
(0.01)
(0.00)
(0.01)
(0.01)
-0.17
-0.05
0.03
0.05
(0.01)
(0.01)
(0.01)
(0.01)
-0.18
-0.06
0.04
0.08
(0.01)
(0.01)
(0.01)
(0.01)
-0.73
-0.31
0.07
0.08
(0.05)
(0.06)
(0.06)
(0.05)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.02
-0.01
0.02
-0.01
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.01
0.01
-0.06
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.04
-0.10
-0.16
-0.21
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.00
0.11
-0.19
-0.12
-0.34
(0.05)
(0.05)
(0.04)
(0.07)
(0.07)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.02
0.00
-0.02
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.03
-0.02
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.05
-0.02
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
-0.15
-0.07
-0.04
-0.26
(0.19)
(0.09)
(0.04)
(0.05)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.04
-0.08
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.10
-0.09
-0.14
-0.20
(0.01)
(0.01)
(0.01)
(0.01)
0.11
-0.09
-0.14
-0.19
(0.01)
(0.01)
(0.01)
(0.01)
0.05
-0.01
-0.16
-0.40
(0.07)
(0.05)
(0.05)
(0.06)
PROXIES
PROXY
ANSPROXY
0.01 (0.01)
0.03 (0.01)
-0.06 (0.01)
-0.05 (0.01)
-0.09 (0.01)
-0.09 (0.01)
-0.08 (0.04)
-0.15 (0.05)
DUAL ELIG
-0.07 (0.01)
0.04 (0.01)
0.04 (0.01)
0.36 (0.04)
89
Table A2b: 2001 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.06
0.03
0.04
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.68
-0.26
0.20
0.34
0.39
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.21
-0.09
0.05
0.07
0.08
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
0.07
-0.09
0.07
0.10
0.11
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.13
-0.11
0.00
0.01
0.00
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.07
0.13
-0.28
-0.43
-0.55
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.11
0.13
-0.20
-0.26
-0.37
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.15
0.15
-0.14
-0.23
-0.27
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.09
0.14
-0.13
-0.18
-0.26
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.20
0.11
-0.05
-0.12
(0.02)
(0.02)
(0.02)
(0.02)
0.31
0.16
-0.12
-0.21
(0.02)
(0.01)
(0.01)
(0.02)
0.25
0.09
-0.04
0.02
(0.02)
(0.01)
(0.01)
(0.02)
0.21
0.08
-0.11
-0.11
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.18
-0.12
-0.19
-0.42
(0.02)
(0.02)
(0.02)
(0.03)
0.28
-0.15
-0.23
-0.46
(0.01)
(0.01)
(0.02)
(0.03)
0.25
-0.12
-0.12
-0.31
(0.01)
(0.01)
(0.02)
(0.03)
0.29
-0.18
-0.27
-0.52
(0.02)
(0.02)
(0.03)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.34 (0.02)
-0.23 (0.03)
-0.17 (0.02)
-0.16 (0.03)
-0.15 (0.02)
-0.26 (0.03)
-0.07 (0.02)
-0.12 (0.04)
DUAL ELIG
0.40 (0.02)
0.05 (0.02)
0.15 (0.02)
0.00 (0.03)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
R-SQUARE
AGE
AGE64
AGE6569
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
0.04
0.04
0.04
0.03
-0.07 (0.01)
-0.01 (0.01)
-0.05 (0.00)
-0.00 (0.00)
90
-0.09 (0.01)
0.02 (0.01)
-0.06 (0.00)
-0.01 (0.00)
AGE7579
AGE8084
AGE85
0.00 (0.01)
-0.00 (0.01)
-0.00 (0.01)
-0.01 (0.00)
-0.01 (0.00)
0.00 (0.01)
0.01 (0.01)
0.02 (0.01)
0.04 (0.01)
0.00 (0.00)
0.00 (0.00)
0.01 (0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.02
-0.03
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.00
-0.02
-0.03
-0.04
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
0.01
0.02
-0.06
-0.04
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.01
-0.01
-0.01
-0.00
-0.01
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.02
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.04
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.04
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.00
0.01
-0.01
-0.02
(0.00)
(0.00)
(0.00)
(0.00)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.06
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.04
-0.12
(0.00)
(0.00)
(0.00)
(0.01)
0.02
-0.01
-0.04
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.01
-0.02
-0.07
(0.00)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
0.01 (0.01)
0.03 (0.01)
0.00 (0.00)
0.03 (0.01)
0.01 (0.01)
-0.00 (0.01)
-0.01 (0.00)
0.03 (0.00)
DUAL ELIG
-0.09 (0.01)
-0.07 (0.00)
-0.05 (0.01)
-0.03 (0.00)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.04
0.04
0.03
0.06
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.07
-0.01
0.01
0.00
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.09
-0.02
-0.00
-0.00
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
0.01
0.02
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.00
0.02
0.02
0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.03
-0.05
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.01
-0.05
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.00
0.01
-0.04
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.02
-0.06
-0.04
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.12
0.06
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.08
0.03
-0.05
-0.05
(0.02)
(0.01)
(0.01)
(0.01)
0.07
0.05
-0.03
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
0.24
0.12
-0.10
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
91
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.04
-0.07
-0.16
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.03 (0.01)
0.01 (0.01)
0.01 (0.02)
-0.04 (0.01)
0.02 (0.01)
-0.02 (0.01)
-0.05 (0.02)
DUAL ELIG
-0.03 (0.01)
-0.06 (0.01)
-0.05 (0.01)
0.04 (0.01)
(0.01)
(0.01)
(0.01)
(0.02)
0.08
-0.03
-0.06
-0.15
(0.01)
(0.01)
(0.01)
(0.02)
0.08
-0.04
-0.05
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.05
-0.02
-0.04
-0.11
(0.01)
(0.01)
(0.01)
(0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
Q28
Provider show
respect
Q29
Provider spend
enough time
R-SQUARE
0.04
0.04
0.04
0.04
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.05
-0.01
0.01
0.01
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.00
-0.01
-0.03
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
-0.01
0.01
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.01
0.00
-0.01
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
0.04
-0.08
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.05
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.03
-0.06
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.05
-0.07
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.10
0.05
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.06
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.06
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.17
0.08
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.09
-0.04
-0.06
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.11
-0.05
-0.09
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.04
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.12
-0.03
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.06 (0.01)
-0.04 (0.01)
-0.06 (0.01)
-0.01 (0.01)
-0.07 (0.01)
-0.02 (0.01)
-0.07 (0.01)
DUAL ELIG
0.01 (0.01)
0.02 (0.01)
0.00 (0.01)
0.02 (0.01)
92
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.06
-0.01
0.02
0.02
0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.06
-0.02
0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.01
-0.03
-0.04
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.02
-0.06
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
0.08
0.04
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.04
-0.04
-0.06
-0.12
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.04
-0.06
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.00)
-0.01 (0.01)
-0.02 (0.01)
-0.03 (0.01)
DUAL ELIG
-0.03 (0.01)
-0.02 (0.01)
CUSTOMER SERVICE, INFORMATION, AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.05
0.05
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.10
-0.00
0.09
0.08
0.02
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.10
-0.03
0.04
0.03
0.06
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
93
-0.10
-0.03
0.01
0.05
0.07
(0.02)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
0.00
-0.09
-0.14
-0.20
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.06
-0.00
-0.03
-0.06
-0.08
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.04
-0.00
-0.07
-0.09
-0.15
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.00
0.01
-0.03
-0.12
(0.04)
(0.02)
(0.02)
(0.03)
0.02
0.00
-0.04
-0.10
(0.02)
(0.01)
(0.01)
(0.02)
0.03
0.05
-0.07
-0.13
(0.03)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.03
-0.16
(0.02)
(0.02)
(0.03)
(0.04)
0.04
-0.06
-0.11
-0.18
(0.01)
(0.01)
(0.02)
(0.02)
0.03
-0.03
-0.07
-0.14
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.09 (0.02)
0.06 (0.04)
-0.10 (0.01)
-0.01 (0.02)
-0.07 (0.02)
0.07 (0.03)
DUAL ELIG
0.02 (0.03)
0.03 (0.01)
0.04 (0.02)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
R-SQUARE
0.05
0.09
0.06
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.03
0.03
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.19
-0.03
0.01
0.03
0.04
(0.03)
(0.03)
(0.03)
(0.03)
(0.02)
-0.15
-0.02
0.03
0.01
0.06
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.01
-0.06
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
0.02
-0.01
-0.13
-0.08
-0.13
(0.02)
(0.02)
(0.02)
(0.03)
(0.03)
-0.00
0.00
-0.07
-0.05
-0.11
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.04
-0.01
-0.06
(0.03)
(0.02)
(0.01)
(0.01)
0.04
0.02
-0.08
-0.20
(0.06)
(0.03)
(0.02)
(0.02)
0.04
0.03
-0.04
-0.12
(0.03)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
0.01 (0.01)
0.02 (0.03)
94
0.05 (0.01)
MHGOOD
MHFAIR
MHPOOR
-0.02 (0.01)
-0.03 (0.01)
-0.07 (0.02)
-0.03 (0.02)
-0.06 (0.02)
-0.14 (0.03)
0.01 (0.01)
-0.03 (0.02)
-0.11 (0.02)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
0.03 (0.01)
-0.05 (0.02)
-0.00 (0.02)
-0.03 (0.01)
0.01 (0.02)
DUAL ELIG
-0.04 (0.01)
0.04 (0.02)
-0.02 (0.01)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.07
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.21
-0.03
0.03
0.04
0.06
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.17
-0.02
0.02
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.02
-0.03
-0.01
-0.04
(0.00)
(0.00)
(0.00)
(0.01)
(0.01)
-0.07
-0.04
0.01
0.03
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.03
-0.06
-0.14
(0.01)
(0.00)
(0.00)
(0.01)
-0.11
-0.01
-0.01
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.02
-0.04
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.03
-0.04
-0.07
-0.11
(0.00)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.00 (0.00)
0.03 (0.01)
0.02 (0.01)
0.05 (0.01)
DUAL ELIG
-0.03 (0.00)
-0.06 (0.01)
95
Table A2c: 2002 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.06
Q7
Personal Dr
Q11
Specialist
0.03
0.03
R-SQUARE
0.07
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-1.13
-0.65
-0.31
0.23
0.37
0.41
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.56
-0.10
-0.08
0.08
0.11
0.13
(0.04)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.04
0.15
-0.08
0.10
0.16
0.12
(0.04)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.31
-0.03
-0.06
0.05
0.08
0.03
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.06
0.14
-0.26
-0.37
-0.53
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.07
0.15
-0.16
-0.25
-0.34
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.11
0.16
-0.09
-0.19
-0.25
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.08
0.15
-0.10
-0.20
-0.23
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.21
0.09
-0.11
-0.28
(0.03)
(0.02)
(0.02)
(0.03)
0.32
0.14
-0.15
-0.29
(0.02)
(0.01)
(0.01)
(0.02)
0.23
0.08
-0.07
-0.07
(0.02)
(0.01)
(0.01)
(0.02)
0.19
0.08
-0.12
-0.23
(0.03)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.16
-0.16
-0.30
-0.57
(0.02)
(0.02)
(0.02)
(0.04)
0.24
-0.16
-0.31
-0.55
(0.01)
(0.01)
(0.02)
(0.03)
0.22
-0.12
-0.23
-0.42
(0.01)
(0.01)
(0.02)
(0.03)
0.25
-0.16
-0.27
-0.49
(0.02)
(0.02)
(0.03)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.31 (0.02)
-0.07 (0.03)
-0.15 (0.02)
-0.08 (0.03)
-0.10 (0.02)
-0.17 (0.03)
-0.09 (0.02)
-0.05 (0.03)
DUAL ELIG
0.46 (0.02)
0.07 (0.02)
0.12 (0.02)
-0.03 (0.02)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
R-SQUARE
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
0.04
0.04
0.04
0.08
96
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.20
-0.07
-0.01
0.01
0.01
0.01
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.12
-0.05
-0.00
0.01
0.01
0.01
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.14
-0.08
0.02
0.00
0.02
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.29
-0.14
-0.03
0.01
0.02
0.04
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
0.00
-0.01
-0.01
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.00
-0.01
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
0.02
-0.05
-0.03
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.02
-0.05
-0.07
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.03
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.06
0.04
-0.00
-0.10
(0.03)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.02
-0.07
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.06
-0.13
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.02
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.06
-0.13
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.00 (0.01)
0.02 (0.01)
0.00 (0.01)
0.01 (0.01)
-0.00 (0.01)
0.03 (0.01)
-0.02 (0.02)
-0.08 (0.03)
DUAL ELIG
-0.08 (0.01)
-0.06 (0.01)
-0.05 (0.01)
-0.08 (0.02)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regulat health
care appt.
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.05
0.04
0.04
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.02
0.01
0.02
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.26
-0.07
-0.02
0.02
0.04
0.07
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.19
-0.01
0.00
0.03
0.06
0.08
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.09
-0.01
-0.00
0.02
0.03
0.04
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
-0.01
0.03
-0.04
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.02
-0.05
-0.01
(0.01)
(0.01)
(0.01)
(0.02)
0.02
0.04
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.05
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
97
COLLMORE
-0.09 (0.01)
-0.08 (0.01)
-0.16 (0.01)
-0.12 (0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.12
0.06
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.10
0.06
-0.05
-0.11
(0.02)
(0.01)
(0.01)
(0.01)
0.15
0.07
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.30
0.12
-0.08
-0.14
(0.02)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.06
-0.10
-0.18
(0.01)
(0.01)
(0.01)
(0.02)
0.04
-0.05
-0.09
-0.13
(0.01)
(0.01)
(0.01)
(0.02)
0.07
-0.03
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
0.02
-0.02
-0.05
-0.03
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
0.01 (0.01)
0.01 (0.01)
0.01 (0.02)
-0.03 (0.01)
0.02 (0.01)
-0.14 (0.01)
0.04 (0.02)
DUAL ELIG
-0.03 (0.01)
-0.00 (0.01)
0.00 (0.01)
0.02 (0.01)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.14
-0.02
-0.00
0.02
0.03
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
0.04
0.01
0.00
-0.01
-0.01
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.13
-0.01
0.00
0.02
0.04
0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.14
0.00
-0.01
0.02
0.01
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
0.04
-0.06
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.04
-0.02
-0.04
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.04
-0.05
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.07
-0.06
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.11
0.06
-0.05
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.06
-0.07
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.05
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.18
0.08
-0.06
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.07
-0.04
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.06
-0.11
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.05
-0.11
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
0.10
-0.06
-0.12
-0.18
(0.01)
(0.01)
(0.01)
(0.02)
98
0.04
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
-0.02 (0.01)
-0.06 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.01 (0.01)
-0.00 (0.01)
DUAL ELIG
0.01 (0.01)
0.02 (0.01)
0.02 (0.01)
0.02 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.01
-0.01
0.02
0.03
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.22
-0.05
-0.02
0.03
0.05
0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.01
-0.03
-0.04
-0.07
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.05
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.01
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
0.09
0.04
-0.04
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.03
-0.07
-0.11
(0.00)
(0.00)
(0.01)
(0.01)
0.06
-0.04
-0.08
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.01 (0.01)
-0.03 (0.01)
-0.02 (0.01)
DUAL ELIG
-0.03 (0.01)
-0.01 (0.01)
CUSTOMER SERVICE, INFORMATION, AND PAPERWORK
Q45
Getting help
from customer
service
R-SQUARE
0.05
Q43
Finding/
understanding
written info
0.06
Q41
Problem with
Medicare
paperwork
0.07
99
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.12
-0.09
-0.04
0.02
0.06
0.08
(0.04)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.15
-0.08
-0.07
0.04
0.07
0.06
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.19
-0.12
-0.05
0.04
0.07
0.06
(0.04)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.00
-0.01
-0.07
-0.12
-0.14
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.05
0.02
-0.03
-0.04
-0.10
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.04
0.02
-0.08
-0.06
-0.18
(0.02)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.00
0.02
-0.07
-0.17
(0.04)
(0.02)
(0.02)
(0.03)
0.05
0.04
-0.04
-0.15
(0.03)
(0.02)
(0.02)
(0.02)
-0.01
0.03
-0.05
-0.14
(0.03)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.05
0.03
0.01
-0.12
(0.02)
(0.02)
(0.03)
(0.04)
0.08
-0.03
-0.11
-0.19
(0.02)
(0.02)
(0.02)
(0.03)
0.03
-0.00
-0.06
-0.10
(0.02)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.07 (0.03)
-0.08 (0.04)
-0.12 (0.02)
0.00 (0.03)
-0.14 (0.02)
0.00 (0.03)
DUAL ELIG
0.02 (0.03)
0.05 (0.02)
0.04 (0.02)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
R-SQUARE
0.07
0.10
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.30
-0.17
-0.03
0.01
0.04
0.07
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.36
-0.21
-0.06
0.02
0.03
0.05
(0.05)
(0.03)
(0.03)
(0.02)
(0.02)
(0.02)
-0.26
-0.18
-0.04
0.01
0.02
0.05
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
-0.04
-0.00
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
0.03
0.05
-0.06
-0.06
(0.02)
(0.02)
(0.02)
(0.03)
-0.01
0.02
-0.04
-0.05
(0.02)
(0.01)
(0.01)
(0.02)
100
COLLMORE
-0.07 (0.02)
-0.13 (0.03)
-0.11 (0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.00
0.04
-0.04
-0.11
(0.03)
(0.01)
(0.01)
(0.01)
0.01
0.05
-0.10
-0.22
(0.05)
(0.03)
(0.02)
(0.02)
-0.02
0.02
-0.03
-0.12
(0.03)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.01
-0.03
-0.06
(0.01)
(0.01)
(0.01)
(0.02)
0.05
0.01
-0.02
-0.13
(0.03)
(0.02)
(0.02)
(0.03)
0.05
-0.03
-0.09
-0.12
(0.01)
(0.01)
(0.02)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
0.02 (0.01)
-0.05 (0.02)
-0.01 (0.02)
-0.03 (0.01)
0.03 (0.02)
DUAL ELIG
-0.04 (0.01)
0.02 (0.02)
-0.04 (0.01)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.08
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.31
-0.21
-0.03
0.03
0.05
0.07
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.31
-0.17
-0.04
0.02
0.03
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.02
-0.03
-0.02
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.08
-0.03
0.01
0.04
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.04
-0.06
-0.15
(0.01)
(0.00)
(0.00)
(0.01)
-0.11
-0.02
-0.02
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.01
-0.05
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.03
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
101
PROXIES
PROXY
ANSPROXY
-0.01 (0.00)
0.03 (0.01)
0.01 (0.01)
0.05 (0.01)
DUAL ELIG
-0.02 (0.00)
-0.05 (0.01)
102
Table A2d: 2003 Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.06
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.07
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.99
-0.72
-0.43
0.30
0.48
0.54
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.68
-0.13
-0.10
0.08
0.12
0.13
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.10
0.12
-0.09
0.09
0.15
0.17
(0.04)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.34
0.03
-0.09
0.07
0.09
0.05
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.11
0.16
-0.26
-0.37
-0.49
(0.02)
(0.02)
(0.02)
(0.03)
(0.02)
0.02
0.07
-0.17
-0.27
-0.32
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.09
0.12
-0.11
-0.22
-0.26
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.01
0.08
-0.11
-0.21
-0.25
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.19
0.11
-0.06
-0.20
(0.03)
(0.02)
(0.02)
(0.03)
0.31
0.14
-0.13
-0.28
(0.03)
(0.02)
(0.01)
(0.02)
0.15
0.07
-0.02
-0.03
(0.02)
(0.01)
(0.01)
(0.02)
0.17
0.07
-0.07
-0.15
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.18
-0.13
-0.23
-0.39
(0.02)
(0.02)
(0.02)
(0.04)
0.24
-0.22
-0.34
-0.61
(0.02)
(0.01)
(0.02)
(0.03)
0.24
-0.17
-0.26
-0.38
(0.01)
(0.01)
(0.02)
(0.03)
0.25
-0.22
-0.33
-0.61
(0.02)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.34 (0.02)
-0.05 (0.03)
-0.14 (0.02)
-0.09 (0.03)
-0.11 (0.02)
-0.12 (0.03)
-0.06 (0.02)
-0.06 (0.03)
DUAL ELIG
0.60 (0.02)
-0.00 (0.02)
0.11 (0.02)
0.02 (0.02)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
R-SQUARE
0.05
Q21
Problem
getting
necessary care
0.05
Q4
Problem
finding a
doctor/nurse
0.04
103
Q22
Problem with
delays in
health care
0.09
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.20
-0.08
-0.01
0.00
-0.00
0.01
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.13
-0.06
-0.01
0.00
0.00
0.01
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.18
-0.07
0.01
0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.34
-0.15
-0.05
0.02
0.01
0.04
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.01
-0.02
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
-0.02
-0.01
-0.04
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.02
0.01
-0.06
-0.05
-0.08
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.04
0.01
-0.07
-0.05
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.02
-0.03
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.02
-0.02
-0.09
(0.01)
(0.00)
(0.00)
(0.01)
0.04
0.03
-0.04
-0.09
(0.01)
(0.01)
(0.00)
(0.01)
0.04
-0.01
-0.02
-0.09
(0.03)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.06
-0.13
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.03
-0.07
-0.12
(0.01)
(0.00)
(0.01)
(0.01)
0.03
-0.01
-0.03
-0.14
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.02 (0.01)
0.00 (0.00)
0.02 (0.01)
-0.00 (0.01)
0.03 (0.01)
-0.06 (0.02)
0.01 (0.03)
DUAL ELIG
-0.11 (0.01)
-0.07 (0.01)
-0.05 (0.01)
-0.13 (0.02)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
0.04
Q16
Getting
regulat health
care appt.
0.04
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.21
-0.03
0.01
0.01
0.02
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.22
-0.06
-0.02
0.02
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.22
-0.04
-0.02
0.01
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.18
-0.05
-0.00
-0.02
-0.04
-0.03
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.00
0.02
-0.04
-0.07
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.01
-0.04
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
-0.01
0.02
-0.05
-0.10
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
-0.02
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
104
0.04
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.10
0.05
-0.04
-0.09
(0.02)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.05
-0.09
(0.02)
(0.01)
(0.01)
(0.01)
0.11
0.05
-0.04
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.21
0.10
-0.06
-0.08
(0.02)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.05
-0.08
-0.11
-0.18
(0.01)
(0.01)
(0.01)
(0.02)
0.07
-0.06
-0.10
-0.15
(0.01)
(0.01)
(0.01)
(0.02)
0.08
-0.06
-0.11
-0.14
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.07
-0.09
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.00 (0.01)
0.01 (0.01)
0.01 (0.02)
-0.01 (0.01)
0.02 (0.01)
-0.05 (0.01)
0.09 (0.02)
DUAL ELIG
-0.03 (0.01)
-0.04 (0.01)
-0.03 (0.01)
-0.01 (0.01)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.15
-0.04
-0.02
0.01
0.02
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.08
0.02
0.00
-0.01
-0.01
-0.01
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.15
-0.04
-0.02
0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.17
-0.01
-0.01
0.00
0.01
0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
0.04
-0.05
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.02
-0.05
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.05
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.06
0.05
-0.06
-0.10
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.10
0.04
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.06
-0.05
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.10
0.05
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.16
0.08
-0.05
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.06
-0.09
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.07
-0.11
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.08
-0.06
-0.10
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.10
-0.07
-0.10
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
-0.02 (0.01)
-0.05 (0.01)
105
0.04
-0.01 (0.01)
0.01 (0.01)
ANSPROXY
-0.03 (0.01)
-0.04 (0.01)
-0.01 (0.01)
-0.02 (0.01)
DUAL ELIG
0.01 (0.01)
0.02 (0.01)
0.01 (0.01)
0.02 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.06
-0.02
0.01
0.02
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.21
-0.05
-0.02
0.02
0.03
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.01
-0.03
-0.04
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.00
0.02
-0.05
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.01
-0.02
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
0.08
0.03
-0.04
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.04
-0.07
-0.11
(0.00)
(0.00)
(0.01)
(0.01)
0.07
-0.06
-0.09
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.00)
-0.01 (0.01)
-0.02 (0.01)
-0.03 (0.01)
DUAL ELIG
-0.04 (0.01)
-0.00 (0.01)
CUSTOMER SERVICE, INFORMATION, AND PAPERWORK
Q45
Getting help
from customer
service
R-SQUARE
0.06
Q43
Finding/
understanding
written info
0.05
Q41
Problem with
Medicare
paperwork
0.07
AGE
106
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.09
-0.08
-0.08
0.01
0.03
0.08
(0.05)
(0.03)
(0.02)
(0.03)
(0.03)
(0.04)
-0.09
-0.05
-0.02
0.02
0.04
0.08
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.03)
-0.01
-0.02
-0.01
0.05
0.07
0.11
(0.04)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
0.02
-0.06
-0.04
-0.14
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.09
-0.00
-0.03
-0.02
-0.07
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.02
-0.00
-0.07
-0.08
-0.16
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.04
-0.07
-0.15
(0.04)
(0.03)
(0.02)
(0.03)
0.09
0.03
-0.03
-0.12
(0.03)
(0.02)
(0.02)
(0.02)
0.03
0.04
-0.01
-0.08
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
-0.03
0.01
-0.05
-0.05
(0.02)
(0.02)
(0.03)
(0.04)
0.02
-0.06
-0.14
-0.21
(0.02)
(0.02)
(0.02)
(0.03)
-0.03
-0.04
-0.12
-0.26
(0.02)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.02 (0.03)
-0.04 (0.04)
-0.07 (0.02)
0.04 (0.03)
-0.16 (0.02)
0.03 (0.03)
DUAL ELIG
-0.05 (0.03)
0.07 (0.02)
0.06 (0.02)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
0.10
Q36
Getting
special
therapy
R-SQUARE
0.06
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.32
-0.16
-0.05
0.01
0.03
0.05
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.36
-0.19
-0.00
0.04
0.04
0.04
(0.04)
(0.03)
(0.03)
(0.02)
(0.02)
(0.02)
-0.35
-0.16
-0.02
0.03
0.03
0.07
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.01
-0.05
-0.05
-0.06
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.03
-0.02
-0.09
-0.07
-0.22
(0.02)
(0.02)
(0.02)
(0.03)
(0.03)
-0.02
0.02
-0.07
-0.04
-0.10
(0.02)
(0.01)
(0.01)
(0.02)
(0.01)
107
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
-0.00
-0.02
-0.07
(0.03)
(0.02)
(0.01)
(0.01)
-0.03
-0.04
-0.05
-0.19
(0.06)
(0.03)
(0.02)
(0.02)
0.03
0.02
-0.03
-0.07
(0.03)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
-0.00
-0.03
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
0.04
-0.04
-0.11
-0.20
(0.02)
(0.02)
(0.02)
(0.03)
0.01
-0.00
-0.08
-0.14
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.03 (0.01)
-0.04 (0.02)
0.01 (0.02)
-0.02 (0.01)
0.02 (0.02)
DUAL ELIG
-0.06 (0.01)
0.04 (0.02)
-0.05 (0.01)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.08
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.37
-0.20
-0.04
0.02
0.04
0.07
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.36
-0.19
-0.03
0.02
0.04
0.06
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.02
-0.04
-0.02
-0.06
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.08
-0.04
-0.02
0.00
-0.02
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.03
-0.06
-0.14
(0.01)
(0.00)
(0.00)
(0.01)
0.04
0.02
-0.05
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.02
-0.07
-0.11
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.03
-0.09
-0.15
(0.00)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
-0.01 (0.01)
0.01 (0.01)
108
ANSPROXY
0.03 (0.01)
0.05 (0.01)
DUAL ELIG
-0.06 (0.01)
-0.08 (0.01)
109
Table A2e: Case-Mix Coefficients, Base Model Plus MHP, With Dual Eligibles, No Regional
Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.06
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.07
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.97
-0.63
-0.36
0.32
0.52
0.63
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.60
-0.20
-0.09
0.06
0.10
0.15
(0.04)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.05
0.11
-0.09
0.10
0.13
0.15
(0.04)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.55
-0.10
-0.11
0.05
0.05
0.09
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.17
0.14
-0.20
-0.30
-0.43
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.06
0.11
-0.12
-0.23
-0.28
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.12
0.15
-0.09
-0.25
-0.26
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.06
0.10
-0.09
-0.18
-0.24
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.24
0.14
-0.09
-0.22
(0.03)
(0.02)
(0.02)
(0.02)
0.27
0.14
-0.11
-0.29
(0.03)
(0.01)
(0.01)
(0.02)
0.16
0.07
-0.03
-0.06
(0.02)
(0.01)
(0.01)
(0.02)
0.08
0.06
-0.07
-0.15
(0.04)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.18
-0.14
-0.24
-0.41
(0.02)
(0.02)
(0.02)
(0.04)
0.23
-0.17
-0.32
-0.48
(0.01)
(0.01)
(0.02)
(0.03)
0.23
-0.16
-0.23
-0.28
(0.01)
(0.01)
(0.02)
(0.03)
0.28
-0.17
-0.32
-0.45
(0.02)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.34 (0.02)
0.05 (0.03)
-0.15 (0.02)
-0.03 (0.02)
-0.09 (0.02)
-0.14 (0.02)
-0.11 (0.02)
-0.06 (0.03)
DUAL ELIG
0.66 (0.02)
-0.01 (0.02)
0.05 (0.02)
-0.02 (0.02)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
R-SQUARE
0.05
Q21
Problem
getting
necessary care
0.05
Q4
Problem
finding a
doctor/nurse
0.04
110
Q22
Problem with
delays in
health care
0.11
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.19
-0.08
-0.02
0.00
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.10
-0.05
-0.00
0.00
0.01
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.16
-0.08
0.00
0.00
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.32
-0.14
-0.05
0.02
0.04
0.08
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.00
-0.02
-0.02
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.00
-0.01
-0.02
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.03
0.03
-0.05
-0.04
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.01
-0.01
-0.04
-0.06
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.02
-0.03
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.01
-0.03
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.03
0.02
-0.03
-0.09
(0.01)
(0.01)
(0.00)
(0.01)
0.06
0.01
-0.03
-0.12
(0.03)
(0.02)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.02
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.02
-0.01
-0.05
-0.13
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.02
-0.05
-0.10
(0.01)
(0.00)
(0.01)
(0.01)
0.01
-0.02
-0.07
-0.17
(0.02)
(0.01)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.01 (0.01)
0.00 (0.01)
0.01 (0.00)
-0.00 (0.01)
0.01 (0.01)
0.03 (0.01)
-0.05 (0.02)
0.00 (0.03)
DUAL ELIG
-0.09 (0.01)
-0.07 (0.00)
-0.06 (0.01)
-0.11 (0.02)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
0.05
Q16
Getting
regular health
care appt.
0.04
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.24
-0.07
-0.02
-0.00
0.00
0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.27
-0.10
-0.01
-0.00
-0.00
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.21
-0.06
-0.02
0.00
0.01
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.18
-0.02
0.01
-0.02
-0.05
-0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.02
-0.03
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.03
-0.04
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.02
-0.05
-0.10
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
-0.00
0.01
-0.03
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
111
0.05
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.08
0.05
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.07
0.04
-0.04
-0.08
(0.02)
(0.01)
(0.01)
(0.01)
0.13
0.06
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.16
0.10
-0.06
-0.08
(0.02)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.07
-0.05
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.04
-0.09
-0.15
(0.01)
(0.01)
(0.01)
(0.02)
0.08
-0.05
-0.09
-0.16
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.06
-0.09
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
0.02 (0.01)
0.00 (0.01)
0.06 (0.02)
-0.00 (0.01)
0.01 (0.01)
-0.05 (0.01)
0.08 (0.02)
DUAL ELIG
-0.06 (0.01)
-0.06 (0.01)
-0.03 (0.01)
-0.06 (0.01)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.16
-0.06
-0.02
-0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
0.00
-0.00
-0.02
-0.03
-0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.14
-0.04
-0.01
0.00
0.01
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.15
-0.03
-0.01
-0.02
-0.00
0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.04
-0.06
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.02
-0.05
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.03
-0.03
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.07
0.06
-0.05
-0.09
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.08
0.04
-0.05
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.06
-0.05
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.09
0.05
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.15
0.07
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.04
-0.08
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.06
-0.11
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.08
-0.05
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.11
-0.06
-0.10
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
-0.02 (0.01)
-0.04 (0.01)
112
0.04
-0.00 (0.01)
-0.01 (0.01)
ANSPROXY
-0.02 (0.01)
-0.03 (0.01)
-0.01 (0.01)
0.00 (0.01)
DUAL ELIG
-0.00 (0.01)
0.01 (0.01)
-0.00 (0.01)
0.00 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.07
-0.02
0.00
0.02
0.03
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.20
-0.07
-0.02
0.00
0.03
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
-0.00
-0.02
-0.04
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.01
-0.05
-0.09
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.00
0.00
-0.02
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.03
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.04
-0.03
-0.06
-0.09
(0.00)
(0.00)
(0.01)
(0.01)
0.07
-0.05
-0.09
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
0.00 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.01 (0.01)
DUAL ELIG
-0.03 (0.01)
-0.03 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
R-SQUARE
0.04
Q43
Finding/
understanding
written info
0.05
Q41
Problem with
Medicare
paperwork
0.07
AGE
113
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.09
-0.01
-0.04
0.00
0.05
0.01
(0.04)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
0.07
0.02
-0.02
0.01
0.05
0.01
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.07
-0.07
-0.03
-0.01
0.01
0.03
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.05
-0.07
-0.08
-0.11
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.02
-0.03
0.01
0.02
0.04
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
-0.03
0.00
-0.05
-0.10
-0.08
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.01
-0.05
-0.17
(0.04)
(0.02)
(0.02)
(0.03)
0.09
0.04
-0.08
-0.15
(0.03)
(0.02)
(0.01)
(0.02)
-0.02
0.01
-0.03
-0.17
(0.04)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.02
-0.06
-0.13
(0.02)
(0.02)
(0.02)
(0.04)
0.07
-0.06
-0.12
-0.23
(0.02)
(0.01)
(0.02)
(0.03)
0.05
-0.02
-0.12
-0.16
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
-0.07 (0.03)
0.12 (0.04)
-0.11 (0.02)
0.09 (0.03)
-0.15 (0.02)
0.04 (0.03)
DUAL ELIG
0.05 (0.02)
0.07 (0.02)
0.00 (0.02)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
0.10
Q36
Getting
special
therapy
0.09
Q38
Getting
prescription
medicines
R-SQUARE
0.07
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.33
-0.14
-0.03
0.03
0.04
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.35
-0.21
-0.03
0.01
0.04
0.02
(0.04)
(0.03)
(0.03)
(0.02)
(0.02)
(0.02)
-0.36
-0.20
-0.04
0.01
0.02
0.05
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
-0.29
-0.21
-0.03
0.03
0.05
0.08
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.00
0.01
-0.03
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.01
0.01
-0.07
-0.04
-0.14
(0.02)
(0.02)
(0.02)
(0.03)
(0.03)
-0.00
-0.00
-0.03
-0.07
-0.08
(0.02)
(0.01)
(0.01)
(0.02)
(0.01)
-0.03
-0.03
-0.02
-0.01
-0.04
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
114
0.09
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.01
-0.01
-0.09
(0.03)
(0.02)
(0.01)
(0.01)
-0.01
0.02
-0.07
-0.18
(0.06)
(0.03)
(0.02)
(0.02)
-0.01
-0.01
-0.03
-0.10
(0.03)
(0.01)
(0.01)
(0.01)
0.05
0.03
-0.07
-0.18
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
0.00
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
0.01
-0.02
-0.07
-0.18
(0.02)
(0.02)
(0.02)
(0.03)
0.02
-0.01
-0.07
-0.17
(0.01)
(0.01)
(0.01)
(0.02)
0.02
-0.01
-0.07
-0.11
(0.00)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.02 (0.01)
-0.01 (0.02)
0.03 (0.02)
-0.04 (0.01)
0.03 (0.02)
-0.02 (0.01)
0.05 (0.01)
DUAL ELIG
-0.08 (0.01)
0.02 (0.02)
-0.04 (0.01)
-0.03 (0.01)
115
Table A2e_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model
Plus MHP, With Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.03
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.13
-0.07
-0.07
0.07
0.11
0.14
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.11
-0.03
-0.03
0.02
0.02
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.05
0.01
-0.03
0.03
0.04
0.05
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.04
0.01
-0.03
0.02
0.01
-0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.08
0.07
-0.07
-0.12
-0.16
(0.00)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.02
-0.03
-0.08
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.03
-0.10
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.00
0.02
0.00
-0.00
(0.00)
(0.00)
(0.00)
(0.01)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.10
0.03
0.00
0.00
(0.01)
(0.00)
(0.00)
(0.01)
-0.04
-0.01
0.02
0.03
(0.01)
(0.00)
(0.00)
(0.01)
0.02
0.00
0.02
0.03
(0.01)
(0.00)
(0.00)
(0.01)
-0.09
-0.05
0.05
0.09
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.02
-0.02
-0.02
(0.00)
(0.00)
(0.00)
(0.01)
0.10
-0.05
-0.06
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.10
-0.04
-0.05
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.05
-0.06
-0.08
(0.00)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.08 (0.00)
-0.03 (0.01)
-0.02 (0.01)
-0.06 (0.01)
-0.01 (0.01)
-0.06 (0.01)
0.01 (0.00)
-0.04 (0.01)
DUAL ELIG
0.16 (0.00)
0.04 (0.00)
0.02 (0.00)
-0.00 (0.00)
116
0.03
Table A3b: 2001 Case-Mix Coefficients, Base Model Plus MHP, No Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.06
0.03
0.04
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.76
-0.27
0.22
0.36
0.42
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.16
-0.09
0.06
0.07
0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.11
-0.10
0.08
0.11
0.13
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.07
-0.12
0.02
0.02
0.01
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.05
0.12
-0.28
-0.43
-0.55
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.09
0.13
-0.20
-0.26
-0.36
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.16
0.15
-0.13
-0.23
-0.26
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.08
0.14
-0.13
-0.19
-0.26
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.19
0.10
-0.06
-0.13
(0.02)
(0.02)
(0.02)
(0.03)
0.31
0.16
-0.13
-0.23
(0.02)
(0.01)
(0.01)
(0.02)
0.24
0.09
-0.05
0.01
(0.02)
(0.01)
(0.02)
(0.03)
0.22
0.08
-0.12
-0.16
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.18
-0.12
-0.19
-0.50
(0.02)
(0.02)
(0.02)
(0.04)
0.28
-0.15
-0.24
-0.48
(0.01)
(0.01)
(0.02)
(0.03)
0.25
-0.12
-0.12
-0.34
(0.01)
(0.01)
(0.02)
(0.04)
0.28
-0.18
-0.28
-0.55
(0.02)
(0.02)
(0.03)
(0.05)
PROXIES
PROXY
ANSPROXY
-0.31 (0.02)
-0.19 (0.03)
-0.13 (0.02)
-0.13 (0.03)
-0.12 (0.02)
-0.23 (0.03)
-0.04 (0.03)
-0.10 (0.04)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
R-SQUARE
AGE
AGE64
AGE6569
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
0.03
0.03
0.03
0.02
-0.08 (0.01)
-0.01 (0.01)
-0.06 (0.01)
-0.00 (0.00)
117
-0.08 (0.01)
0.02 (0.01)
-0.07 (0.00)
-0.01 (0.00)
AGE7579
AGE8084
AGE85
0.01 (0.01)
-0.00 (0.01)
-0.01 (0.01)
-0.01 (0.00)
-0.01 (0.00)
0.00 (0.00)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.02
-0.02
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.01
-0.02
-0.03
-0.04
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
0.00
0.01
-0.05
-0.04
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.02
-0.01
-0.01
-0.00
-0.01
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.02
-0.03
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.04
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.03
-0.04
-0.10
(0.01)
(0.00)
(0.01)
(0.01)
0.00
0.01
-0.01
-0.02
(0.00)
(0.00)
(0.00)
(0.00)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.03
-0.06
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.04
-0.11
(0.00)
(0.00)
(0.00)
(0.01)
0.02
-0.01
-0.04
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.01
-0.02
-0.06
(0.00)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.04 (0.01)
0.00 (0.00)
0.03 (0.01)
0.01 (0.01)
0.02 (0.01)
0.03 (0.01)
0.01 (0.01)
-0.00 (0.01)
0.00 (0.00)
-0.00 (0.00)
0.00 (0.00)
-0.01 (0.00)
0.03 (0.01)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.04
0.04
0.03
0.06
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.05
-0.00
0.01
0.00
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.08
-0.03
0.00
-0.01
-0.00
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.01
0.01
0.02
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.01
0.02
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.03
-0.05
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.00
-0.04
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.00
0.02
-0.04
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.02
-0.05
-0.04
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.13
0.07
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
0.08
0.04
-0.05
-0.07
(0.02)
(0.01)
(0.01)
(0.01)
0.07
0.05
-0.04
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
0.25
0.12
-0.10
-0.17
(0.01)
(0.01)
(0.01)
(0.02)
118
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.05
-0.08
-0.14
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.03 (0.02)
(0.01)
(0.01)
(0.01)
(0.02)
0.07
-0.04
-0.07
-0.14
(0.01)
(0.01)
(0.01)
(0.02)
0.02 (0.01)
0.02 (0.02)
0.08
-0.04
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
-0.02 (0.01)
0.01 (0.01)
0.04
-0.02
-0.04
-0.11
(0.01)
(0.01)
(0.01)
(0.02)
-0.01 (0.01)
-0.06 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.04
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.03
-0.01
0.01
0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
-0.00
-0.01
-0.03
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.01
0.01
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
-0.01
0.00
-0.01
0.02
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.04
-0.07
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.04
-0.04
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.06
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.04
-0.07
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.11
0.06
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.06
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.06
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.18
0.09
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.09
-0.04
-0.07
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.11
-0.05
-0.09
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.04
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.12
-0.03
-0.07
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.06 (0.01)
-0.04 (0.01)
-0.07 (0.01)
OFFICE STAFF
R-SQUARE
Q24
Office staff
courteous
Q25
Office staff
helpful
0.02
0.04
119
0.04
-0.00 (0.01)
-0.07 (0.01)
-0.01 (0.01)
-0.06 (0.01)
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.06
-0.02
0.02
0.02
0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.05
-0.02
0.02
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.01
-0.03
-0.04
-0.06
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.01
0.02
-0.06
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.02
-0.02
(0.01)
(0.00)
(0.00)
(0.01)
0.09
0.05
-0.03
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.04
-0.03
-0.06
-0.12
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.04
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
-0.00 (0.01)
-0.02 (0.01)
-0.04 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.05
0.05
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.10
-0.01
0.10
0.08
0.03
(0.03)
(0.02)
(0.02)
(0.03)
(0.04)
-0.10
-0.03
0.04
0.03
0.06
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.12
-0.03
0.01
0.04
0.06
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.07
0.01
-0.09
-0.13
-0.20
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.08
-0.01
-0.03
-0.06
-0.08
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.04
-0.02
-0.06
-0.09
-0.15
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
-0.00 (0.04)
0.02 (0.02)
120
0.04 (0.03)
VERYGOOD
FAIR
POOR
0.00 (0.02)
-0.02 (0.02)
-0.10 (0.03)
0.01 (0.01)
-0.04 (0.01)
-0.10 (0.02)
0.05 (0.02)
-0.07 (0.02)
-0.13 (0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.06
-0.17
0.04
-0.06
-0.11
-0.19
0.03
-0.03
-0.07
-0.13
PROXIES
PROXY
ANSPROXY
-0.10 (0.03)
0.08 (0.04)
(0.02)
(0.02)
(0.03)
(0.04)
(0.01)
(0.01)
(0.02)
(0.03)
-0.09 (0.02)
0.01 (0.03)
(0.02)
(0.02)
(0.02)
(0.04)
-0.06 (0.02)
0.06 (0.03)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
R-SQUARE
0.05
0.11
0.07
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.19
-0.03
0.03
0.02
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
-0.23
-0.05
0.00
0.01
0.02
(0.04)
(0.04)
(0.03)
(0.03)
(0.03)
-0.16
-0.02
0.03
0.01
0.06
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
0.01
-0.05
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
0.02
-0.01
-0.12
-0.07
-0.12
(0.03)
(0.03)
(0.02)
(0.04)
(0.04)
-0.02
-0.01
-0.08
-0.05
-0.12
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.04
-0.00
-0.07
(0.03)
(0.02)
(0.01)
(0.01)
0.06
0.02
-0.09
-0.24
(0.07)
(0.03)
(0.02)
(0.03)
0.04
0.03
-0.04
-0.13
(0.03)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.02
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
0.01
-0.03
-0.08
-0.14
(0.03)
(0.03)
(0.03)
(0.03)
0.04
0.01
-0.04
-0.11
(0.01)
(0.01)
(0.02)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.03 (0.02)
-0.06 (0.02)
0.02 (0.03)
121
-0.03 (0.01)
0.02 (0.02)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.07
0.03
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.22
-0.02
0.03
0.04
0.05
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.19
-0.03
0.02
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.03
-0.02
-0.01
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.09
-0.04
0.01
0.03
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.03
-0.06
-0.13
(0.01)
(0.00)
(0.00)
(0.01)
-0.11
-0.01
-0.01
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.02
-0.05
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.03
-0.04
-0.07
-0.11
(0.00)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.00 (0.00)
0.03 (0.01)
0.02 (0.01)
0.06 (0.01)
122
Table A3c: 2002 Case-Mix Coefficients, Base Model Plus MHP, No Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.08
0.06
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-1.39
-0.72
-0.31
0.25
0.41
0.46
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.54
-0.06
-0.07
0.08
0.12
0.13
(0.05)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
0.08
0.21
-0.08
0.10
0.17
0.13
(0.05)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.28
0.02
-0.06
0.07
0.09
0.04
(0.06)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.06
0.11
-0.25
-0.37
-0.53
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.08
0.13
-0.14
-0.23
-0.34
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.10
0.15
-0.09
-0.20
-0.25
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.08
0.12
-0.10
-0.19
-0.23
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.21
0.08
-0.11
-0.29
(0.02)
(0.02)
(0.02)
(0.03)
0.32
0.14
-0.17
-0.32
(0.02)
(0.01)
(0.01)
(0.03)
0.22
0.08
-0.09
-0.07
(0.02)
(0.01)
(0.02)
(0.03)
0.20
0.08
-0.15
-0.22
(0.03)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.17
-0.16
-0.33
-0.67
(0.02)
(0.02)
(0.02)
(0.04)
0.24
-0.14
-0.32
-0.53
(0.01)
(0.01)
(0.02)
(0.04)
0.22
-0.12
-0.22
-0.41
(0.01)
(0.01)
(0.02)
(0.04)
0.26
-0.14
-0.27
-0.53
(0.02)
(0.02)
(0.03)
(0.05)
PROXIES
PROXY
ANSPROXY
-0.27 (0.02)
-0.06 (0.03)
-0.10 (0.02)
-0.09 (0.03)
-0.07 (0.02)
-0.16 (0.03)
-0.05 (0.02)
-0.04 (0.04)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
R-SQUARE
AGE
AGE44
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
0.04
0.04
0.04
0.08
-0.20 (0.02)
-0.15 (0.01)
123
-0.13 (0.02)
-0.35 (0.04)
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.07
-0.01
0.00
0.00
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
-0.00
0.01
0.00
0.00
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.06
0.02
0.01
0.03
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.15
-0.02
0.01
0.01
0.04
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.00
-0.01
-0.01
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
-0.01
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.01
-0.04
-0.03
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.01
0.02
-0.04
-0.06
-0.08
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.04
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.01
-0.02
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.06
0.03
-0.04
-0.10
(0.01)
(0.00)
(0.01)
(0.01)
0.04
0.03
-0.01
-0.10
(0.03)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.02
-0.07
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.06
-0.13
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.01
-0.06
-0.11
(0.01)
(0.00)
(0.01)
(0.01)
0.02
-0.03
-0.08
-0.14
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.02 (0.01)
0.01 (0.01)
0.01 (0.01)
-0.00 (0.01)
0.03 (0.01)
0.00 (0.02)
-0.10 (0.03)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.04
0.04
0.04
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.01
0.01
0.02
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.25
-0.07
-0.02
0.01
0.05
0.06
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.19
-0.02
0.00
0.03
0.06
0.07
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
0.01
0.00
0.02
0.03
0.04
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.00
0.03
-0.04
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.03
-0.04
-0.01
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
0.02
0.03
-0.06
-0.10
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.05
-0.05
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
0.12 (0.01)
0.06 (0.01)
0.11 (0.02)
0.06 (0.01)
124
0.15 (0.01)
0.08 (0.01)
0.30 (0.02)
0.13 (0.01)
FAIR
POOR
-0.07 (0.01)
-0.11 (0.01)
-0.06 (0.01)
-0.12 (0.02)
-0.07 (0.01)
-0.11 (0.01)
-0.09 (0.01)
-0.16 (0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.05
-0.10
-0.17
0.04
-0.04
-0.09
-0.12
0.07
-0.03
-0.07
-0.11
0.03
-0.01
-0.04
-0.02
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.01 (0.01)
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
0.00 (0.01)
0.04 (0.02)
(0.01)
(0.01)
(0.01)
(0.02)
-0.01 (0.01)
0.01 (0.01)
(0.01)
(0.01)
(0.01)
(0.03)
-0.11 (0.01)
0.05 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.05
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.13
-0.01
-0.00
0.02
0.04
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.08
0.05
0.02
0.01
-0.01
-0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.12
0.00
0.00
0.02
0.04
0.06
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.11
0.02
-0.00
0.02
0.02
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.04
-0.06
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.04
-0.02
-0.03
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.04
-0.04
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.07
-0.06
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.11
0.06
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.06
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.05
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.18
0.09
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.04
-0.09
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.05
-0.10
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.04
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.10
-0.05
-0.11
-0.17
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.02 (0.01)
-0.05 (0.01)
-0.01 (0.01)
125
0.05
-0.02 (0.01)
-0.02 (0.01)
-0.00 (0.01)
0.00 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.21
-0.05
-0.01
0.02
0.03
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.22
-0.04
-0.02
0.03
0.05
0.06
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.01
-0.03
-0.03
-0.07
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.03
-0.04
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.01
-0.02
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
0.09
0.04
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.03
-0.07
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.07
-0.03
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
0.00 (0.01)
-0.03 (0.01)
-0.02 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.06
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.16
-0.09
-0.04
0.02
0.04
0.07
(0.05)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.16
-0.08
-0.06
0.04
0.06
0.07
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
126
-0.20
-0.12
-0.04
0.04
0.08
0.05
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
-0.02
-0.05
-0.11
-0.14
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.05
0.02
-0.03
-0.04
-0.10
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.07
0.03
-0.07
-0.05
-0.18
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.02
0.01
-0.06
-0.17
(0.04)
(0.02)
(0.02)
(0.03)
0.05
0.04
-0.04
-0.16
(0.03)
(0.02)
(0.02)
(0.03)
-0.01
0.03
-0.05
-0.17
(0.03)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
0.02
-0.01
-0.14
(0.02)
(0.02)
(0.03)
(0.05)
0.07
-0.04
-0.12
-0.19
(0.02)
(0.02)
(0.02)
(0.04)
0.02
-0.01
-0.07
-0.12
(0.02)
(0.02)
(0.03)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.05 (0.03)
-0.08 (0.04)
-0.13 (0.02)
0.01 (0.03)
-0.13 (0.02)
0.03 (0.03)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
R-SQUARE
0.06
0.12
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.34
-0.17
-0.02
0.01
0.04
0.06
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.36
-0.25
-0.03
0.03
0.05
0.06
(0.06)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
-0.31
-0.19
-0.04
0.02
0.03
0.05
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.02
-0.03
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.01
0.04
-0.03
-0.03
-0.13
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.02
0.01
-0.04
-0.05
-0.11
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.03
-0.04
-0.10
(0.03)
(0.01)
(0.01)
(0.01)
0.02
0.05
-0.10
-0.22
(0.06)
(0.03)
(0.02)
(0.03)
-0.03
0.01
-0.04
-0.12
(0.03)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
0.01 (0.01)
-0.01 (0.01)
0.03 (0.03)
0.02 (0.02)
127
0.05 (0.01)
-0.04 (0.01)
MHFAIR
MHPOOR
-0.04 (0.01)
-0.08 (0.02)
-0.03 (0.03)
-0.15 (0.03)
-0.10 (0.02)
-0.13 (0.02)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
0.02 (0.02)
-0.07 (0.02)
0.01 (0.03)
-0.02 (0.01)
0.03 (0.02)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.08
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.39
-0.22
-0.02
0.03
0.05
0.07
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.38
-0.18
-0.04
0.01
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.03
-0.03
-0.01
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.08
-0.04
0.01
0.04
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.04
-0.06
-0.15
(0.01)
(0.00)
(0.00)
(0.01)
-0.10
-0.02
-0.02
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.01
-0.05
-0.11
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.03
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.00)
0.03 (0.01)
0.02 (0.01)
0.05 (0.01)
128
Table A3d: 2003 Case-Mix Coefficients, Base Model Plus MHP, No Dual Eligibles, No
Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.06
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-1.21
-0.83
-0.44
0.33
0.51
0.60
(0.06)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.61
-0.12
-0.11
0.08
0.11
0.12
(0.05)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
0.07
0.14
-0.09
0.11
0.16
0.18
(0.05)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.28
0.07
-0.10
0.09
0.10
0.03
(0.06)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.07
0.15
-0.24
-0.37
-0.49
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.01
0.08
-0.17
-0.29
-0.32
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.09
0.12
-0.11
-0.23
-0.26
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
-0.01
0.08
-0.11
-0.23
-0.25
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.17
0.12
-0.05
-0.19
(0.03)
(0.02)
(0.02)
(0.03)
0.29
0.14
-0.12
-0.28
(0.03)
(0.01)
(0.01)
(0.02)
0.15
0.07
-0.01
-0.02
(0.02)
(0.01)
(0.01)
(0.02)
0.14
0.07
-0.06
-0.16
(0.03)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.19
-0.15
-0.29
-0.41
(0.02)
(0.02)
(0.02)
(0.04)
0.25
-0.22
-0.38
-0.59
(0.01)
(0.01)
(0.02)
(0.03)
0.25
-0.17
-0.30
-0.37
(0.01)
(0.01)
(0.02)
(0.04)
0.26
-0.22
-0.36
-0.59
(0.02)
(0.02)
(0.03)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.31 (0.02)
-0.04 (0.03)
-0.10 (0.02)
-0.06 (0.03)
0.04
-0.09 (0.02)
-0.10 (0.03)
-0.04 (0.02)
-0.06 (0.03)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
R-SQUARE
AGE
AGE44
0.04
-0.25 (0.02)
Q21
Problem
getting
necessary care
0.04
Q4
Problem
finding a
doctor/nurse
0.04
-0.19 (0.01)
129
-0.16 (0.02)
Q22
Problem with
delays in
health care
0.08
-0.34 (0.04)
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.07
-0.01
0.00
-0.01
-0.00
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.01
0.00
-0.00
0.01
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.06
0.01
0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.11
-0.02
0.05
0.05
0.06
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.01
-0.02
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
-0.02
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.00)
0.01
0.01
-0.05
-0.05
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.07
-0.01
-0.06
-0.06
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.02
-0.03
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.01
-0.02
-0.09
(0.01)
(0.00)
(0.00)
(0.01)
0.04
0.03
-0.04
-0.08
(0.01)
(0.00)
(0.00)
(0.01)
0.03
0.01
-0.01
-0.07
(0.03)
(0.02)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.08
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.02
-0.06
-0.14
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.03
-0.08
-0.12
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.02
-0.06
-0.21
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.02 (0.01)
0.01 (0.00)
0.01 (0.01)
0.00 (0.01)
0.03 (0.01)
-0.04 (0.02)
0.01 (0.03)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.23
-0.03
0.00
0.02
0.02
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.20
-0.05
-0.02
0.02
0.02
0.03
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.23
-0.03
-0.02
0.02
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.17
-0.02
-0.00
-0.01
-0.04
-0.04
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.00
0.02
-0.04
-0.07
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.01
-0.03
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.03
-0.05
-0.10
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.01
-0.01
-0.06
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.09 (0.01)
0.04 (0.01)
0.03
Q23
Waiting 15
minutes past
appt.
R-SQUARE
GHP
EXCEL
VERYGOOD
0.04
Q16
Getting
regular health
care appt.
0.02 (0.02)
0.03 (0.01)
130
0.05
0.11 (0.01)
0.05 (0.01)
0.21 (0.02)
0.10 (0.01)
FAIR
POOR
-0.04 (0.01)
-0.10 (0.01)
-0.05 (0.01)
-0.09 (0.01)
-0.05 (0.01)
-0.07 (0.01)
-0.07 (0.01)
-0.09 (0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.05
-0.07
-0.12
-0.17
0.08
-0.06
-0.11
-0.14
0.09
-0.06
-0.11
-0.12
0.07
-0.08
-0.10
-0.08
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.00 (0.01)
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
0.01 (0.01)
0.02 (0.02)
(0.01)
(0.01)
(0.01)
(0.02)
0.00 (0.01)
0.01 (0.01)
(0.01)
(0.01)
(0.01)
(0.02)
-0.04 (0.01)
0.09 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
Q27
Provider
explain things
0.04
Q28
Provider show
respect
0.04
Q29
Provider spend
enough time
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.13
-0.03
-0.02
0.01
0.02
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
0.04
0.00
-0.01
-0.02
-0.01
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.13
-0.02
-0.02
0.01
0.02
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.11
0.01
-0.01
0.01
0.01
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.04
-0.05
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.02
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.05
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.05
-0.06
-0.10
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.10
0.04
-0.05
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.06
-0.05
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.09
0.04
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.17
0.08
-0.06
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.06
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.09
-0.07
-0.12
-0.16
(0.01)
(0.01)
(0.01)
(0.01)
0.08
-0.06
-0.10
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
0.10
-0.07
-0.11
-0.15
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
-0.02 (0.01)
-0.05 (0.01)
-0.03 (0.01)
131
0.04
-0.02 (0.01)
0.00 (0.01)
0.01 (0.01)
-0.01 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.05
-0.02
0.01
0.02
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.20
-0.05
-0.02
0.02
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.00
-0.03
-0.04
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.00
0.02
-0.05
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.01
-0.02
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
0.09
0.03
-0.04
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.04
-0.07
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.07
-0.05
-0.09
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
0.00 (0.01)
-0.02 (0.01)
-0.01 (0.01)
-0.03 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
R-SQUARE
0.06
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.08
-0.06
-0.06
0.02
0.04
0.07
Q43
Finding/
understanding
written info
0.05
(0.06)
(0.03)
(0.02)
(0.03)
(0.03)
(0.04)
-0.12
-0.06
-0.02
0.02
0.02
0.08
Q41
Problem with
Medicare
paperwork
0.08
(0.05)
(0.02)
(0.02)
(0.02)
(0.02)
(0.03)
132
-0.05
-0.01
0.01
0.06
0.08
0.09
(0.05)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.06
0.03
-0.04
-0.06
-0.14
(0.04)
(0.03)
(0.02)
(0.03)
(0.03)
-0.11
-0.01
-0.03
-0.02
-0.07
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.04
-0.01
-0.08
-0.09
-0.16
(0.03)
(0.03)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.05
-0.05
-0.15
(0.04)
(0.02)
(0.02)
(0.03)
0.08
0.03
-0.04
-0.12
(0.03)
(0.02)
(0.02)
(0.02)
0.03
0.06
0.00
-0.08
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
-0.02
0.02
-0.07
-0.04
(0.02)
(0.02)
(0.03)
(0.05)
0.03
-0.05
-0.15
-0.18
(0.02)
(0.02)
(0.02)
(0.04)
-0.02
-0.03
-0.13
-0.24
(0.02)
(0.02)
(0.03)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.01 (0.03)
-0.05 (0.04)
-0.06 (0.02)
0.05 (0.03)
-0.14 (0.02)
0.02 (0.03)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
0.12
Q36
Getting
special
therapy
R-SQUARE
0.06
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.31
-0.17
-0.04
0.02
0.04
0.05
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.37
-0.21
0.04
0.05
0.05
0.04
(0.06)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
-0.35
-0.18
-0.01
0.03
0.04
0.07
(0.04)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.01
-0.04
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
-0.04
-0.01
-0.06
-0.03
-0.17
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.04
0.00
-0.06
-0.03
-0.08
(0.02)
(0.01)
(0.01)
(0.02)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.00
-0.03
-0.07
(0.03)
(0.02)
(0.01)
(0.01)
-0.14
-0.05
-0.05
-0.19
(0.07)
(0.03)
(0.02)
(0.02)
0.02
0.03
-0.03
-0.08
(0.03)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
0.00 (0.01)
-0.03 (0.01)
0.04 (0.03)
-0.05 (0.02)
133
0.00 (0.01)
-0.01 (0.01)
MHFAIR
MHPOOR
-0.05 (0.01)
-0.08 (0.02)
-0.13 (0.02)
-0.21 (0.03)
-0.09 (0.01)
-0.13 (0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
0.02 (0.01)
-0.06 (0.02)
0.04 (0.02)
-0.00 (0.01)
-0.00 (0.02)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.08
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.48
-0.21
-0.04
0.02
0.03
0.05
(0.02)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.48
-0.19
-0.02
0.02
0.03
0.05
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.02
-0.03
-0.02
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.08
-0.04
-0.01
0.00
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.05
0.02
-0.05
-0.14
(0.01)
(0.00)
(0.00)
(0.01)
0.03
0.02
-0.04
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.09
-0.12
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.03
-0.10
-0.14
(0.00)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
0.03 (0.01)
0.00 (0.01)
0.06 (0.01)
134
Table A3b_d: 2001 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.03
0.03
0.02
AGE
AGE64
AGE6569
AGE7579
AGE8084
AGE85
-0.11
-0.08
0.05
0.09
0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.02
-0.04
0.02
0.02
0.00
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
-0.04
0.03
0.03
0.04
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.03
0.01
-0.00
-0.03
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.06
0.07
-0.09
-0.16
-0.20
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
0.03
-0.05
-0.09
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
0.04
-0.04
-0.10
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.01
0.01
0.01
0.00
(0.00)
(0.00)
(0.00)
(0.01)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.08
0.03
0.00
0.01
(0.01)
(0.00)
(0.00)
(0.01)
-0.03
-0.01
0.01
0.03
(0.01)
(0.00)
(0.00)
(0.01)
0.04
0.01
0.01
0.04
(0.01)
(0.00)
(0.00)
(0.01)
-0.10
-0.05
0.05
0.09
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.09
-0.02
-0.02
-0.04
(0.00)
(0.00)
(0.01)
(0.01)
0.11
-0.04
-0.05
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.10
-0.02
-0.03
-0.06
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.04
-0.06
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.08 (0.01)
-0.08 (0.01)
-0.03 (0.01)
-0.06 (0.01)
135
-0.02 (0.01)
-0.04 (0.01)
0.02 (0.00)
-0.03 (0.01)
Table A3c_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model
Plus MHP, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.03
0.03
0.02
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.16
-0.08
-0.07
0.07
0.11
0.12
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.09
0.01
-0.03
0.03
0.03
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.01
0.04
-0.03
0.03
0.05
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
0.03
-0.02
0.02
0.01
-0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.05
0.07
-0.08
-0.16
-0.20
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
0.03
-0.03
-0.08
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.03
-0.09
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.00
0.01
-0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.09
0.02
-0.01
-0.02
(0.01)
(0.00)
(0.00)
(0.01)
-0.01
0.00
0.01
0.01
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.01
0.00
0.02
(0.01)
(0.00)
(0.00)
(0.01)
-0.08
-0.04
0.04
0.07
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.03
-0.05
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.10
-0.03
-0.06
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.03
-0.05
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.04
-0.06
-0.09
(0.00)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.06 (0.01)
-0.04 (0.01)
-0.01 (0.01)
-0.06 (0.01)
136
0.01 (0.01)
-0.06 (0.01)
0.03 (0.00)
-0.04 (0.01)
Table A3d_d: 2003 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, No Dual Eligibles, No Regional Interactions, Geo Unit Reporting Entities
Q46
Medicare
Q30
Heakth Care
0.03
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.07
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.11
-0.09
-0.08
0.07
0.11
0.14
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.10
-0.01
-0.03
0.02
0.03
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.03
0.03
-0.04
0.03
0.05
0.06
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.04
0.02
-0.03
0.02
0.01
-0.03
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.07
0.08
-0.08
-0.14
-0.17
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.00
0.02
-0.04
-0.09
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.03
-0.04
-0.09
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.01
0.01
-0.01
0.00
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.08
0.03
0.01
0.00
(0.01)
(0.00)
(0.00)
(0.01)
-0.06
-0.01
0.02
0.02
(0.01)
(0.00)
(0.00)
(0.01)
0.00
0.00
0.01
0.04
(0.01)
(0.00)
(0.00)
(0.01)
-0.11
-0.04
0.05
0.08
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.08
-0.02
-0.03
-0.03
(0.00)
(0.00)
(0.01)
(0.01)
0.12
-0.06
-0.07
-0.11
(0.00)
(0.00)
(0.01)
(0.01)
0.11
-0.05
-0.07
-0.09
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.05
-0.06
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.08 (0.01)
-0.04 (0.01)
-0.01 (0.01)
-0.06 (0.01)
137
0.03
-0.01 (0.01)
-0.05 (0.01)
0.03 (0.00)
-0.05 (0.01)
Table A4c: 2002 Case-Mix Coefficients, Base Model Plus MHP, Plus Life Satisfaction, No Dual
Eligibles, No Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.08
0.07
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-1.39
-0.71
-0.32
0.26
0.42
0.47
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.54
-0.06
-0.08
0.09
0.13
0.14
(0.05)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
0.08
0.21
-0.09
0.10
0.18
0.14
(0.05)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.28
0.03
-0.06
0.07
0.10
0.06
(0.06)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.06
0.12
-0.25
-0.39
-0.56
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.08
0.14
-0.15
-0.25
-0.36
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.11
0.15
-0.09
-0.21
-0.27
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.09
0.13
-0.10
-0.20
-0.25
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.02
-0.03
-0.01
-0.04
(0.03)
(0.02)
(0.02)
(0.04)
0.10
0.05
-0.09
-0.14
(0.03)
(0.02)
(0.02)
(0.03)
0.02
-0.00
-0.03
0.03
(0.03)
(0.02)
(0.02)
(0.03)
0.05
0.02
-0.09
-0.05
(0.04)
(0.02)
(0.02)
(0.04)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.12
-0.12
-0.25
-0.52
(0.02)
(0.02)
(0.02)
(0.04)
0.19
-0.11
-0.26
-0.42
(0.01)
(0.01)
(0.02)
(0.04)
0.18
-0.09
-0.18
-0.35
(0.01)
(0.01)
(0.02)
(0.04)
0.22
-0.12
-0.23
-0.43
(0.02)
(0.02)
(0.03)
(0.05)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.42
0.20
-0.14
-0.42
(0.03)
(0.02)
(0.02)
(0.04)
0.40
0.17
-0.10
-0.30
(0.02)
(0.01)
(0.02)
(0.03)
0.36
0.14
-0.07
-0.13
(0.02)
(0.02)
(0.02)
(0.03)
0.28
0.09
-0.08
-0.31
(0.03)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.27 (0.02)
-0.06 (0.03)
-0.10 (0.02)
-0.09 (0.03)
138
-0.07 (0.02)
-0.16 (0.03)
-0.05 (0.02)
-0.03 (0.03)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
R-SQUARE
0.04
0.04
0.04
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.20
-0.07
-0.01
0.01
0.01
0.01
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.15
-0.06
-0.00
0.01
0.01
0.00
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.13
-0.06
0.02
0.01
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.35
-0.15
-0.03
0.01
0.02
0.04
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.00
-0.01
-0.01
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.03
-0.00
-0.01
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.01
-0.04
-0.03
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.01
0.02
-0.05
-0.06
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.00
0.00
-0.01
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.01
-0.00
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
0.03
0.02
-0.02
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
-0.00
0.01
0.00
-0.04
(0.03)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.00
-0.01
-0.04
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.00
-0.02
-0.05
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.00
-0.04
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.00
-0.02
-0.06
-0.11
(0.02)
(0.02)
(0.02)
(0.03)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.05
0.03
-0.05
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.04
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.02
-0.04
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.08
0.04
-0.01
-0.11
(0.03)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.03 (0.01)
0.01 (0.01)
0.01 (0.01)
-0.00 (0.01)
0.03 (0.01)
-0.00 (0.02)
-0.10 (0.03)
GETTING CARE QUICKLY
R-SQUARE
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
0.05
0.05
0.04
0.05
139
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.01
0.01
0.02
0.04
0.06
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.25
-0.07
-0.02
0.02
0.05
0.07
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.19
-0.01
0.00
0.03
0.06
0.08
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.07
0.01
0.00
0.02
0.04
0.04
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.01
0.03
-0.04
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.01
0.03
-0.04
-0.01
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
0.02
0.04
-0.06
-0.10
-0.17
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.05
-0.05
-0.08
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.03
-0.04
-0.03
(0.01)
(0.01)
(0.01)
(0.02)
0.06
0.03
-0.02
-0.03
(0.02)
(0.01)
(0.01)
(0.02)
0.08
0.05
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
0.22
0.09
-0.06
-0.09
(0.02)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.05
-0.04
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.02)
0.03
-0.03
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.02
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
0.00
-0.00
-0.02
0.01
(0.01)
(0.01)
(0.01)
(0.03)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.11
0.05
-0.05
-0.14
(0.01)
(0.01)
(0.01)
(0.02)
0.09
0.05
-0.06
-0.15
(0.02)
(0.01)
(0.01)
(0.02)
0.13
0.05
-0.05
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
0.15
0.05
-0.04
-0.11
(0.02)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.01 (0.01)
0.00 (0.01)
0.04 (0.02)
-0.02 (0.01)
0.01 (0.01)
-0.11 (0.01)
0.05 (0.02)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.13
-0.01
-0.00
0.03
0.04
0.04
EDUCATION
LESS8GRD
Q27
Provider
explain things
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04 (0.01)
-0.08
0.06
0.02
0.01
-0.00
-0.01
Q28
Provider show
respect
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02 (0.01)
140
-0.12
0.01
0.00
0.03
0.05
0.06
Q29
Provider spend
enough time
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04 (0.01)
-0.11
0.03
-0.00
0.02
0.03
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05 (0.01)
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
-0.06
-0.07
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.04
-0.02
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.04
-0.04
-0.05
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.07
-0.06
-0.08
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.03
-0.04
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.03
-0.05
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.02
-0.03
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
0.09
0.04
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.03
-0.07
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.08
-0.04
-0.09
-0.13
(0.01)
(0.01)
(0.01)
(0.02)
0.07
-0.03
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
0.07
-0.03
-0.08
-0.13
(0.01)
(0.01)
(0.01)
(0.02)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.13
0.05
-0.03
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.13
0.06
-0.03
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.13
0.05
-0.04
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.18
0.07
-0.05
-0.12
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
-0.02 (0.01)
-0.05 (0.01)
-0.01 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.21
-0.05
-0.01
0.02
0.03
0.05
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.22
-0.04
-0.02
0.04
0.05
0.07
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.01
0.01
-0.03
-0.04
-0.07
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.05
-0.07
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.00
-0.00
-0.01
-0.00
(0.01)
(0.00)
(0.00)
(0.01)
0.03
0.01
-0.02
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
141
-0.02 (0.01)
-0.02 (0.01)
-0.00 (0.01)
0.00 (0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.02
-0.06
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.05
-0.03
-0.07
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.06
0.02
-0.02
-0.06
(0.01)
(0.00)
(0.01)
(0.01)
0.11
0.04
-0.03
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
0.00 (0.01)
-0.03 (0.01)
-0.02 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
R-SQUARE
0.06
0.06
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.15
-0.09
-0.05
0.02
0.04
0.07
(0.05)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.16
-0.08
-0.06
0.04
0.07
0.07
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.20
-0.12
-0.04
0.04
0.07
0.05
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
-0.02
-0.05
-0.11
-0.15
(0.03)
(0.03)
(0.02)
(0.03)
(0.03)
-0.05
0.02
-0.03
-0.04
-0.11
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.07
0.03
-0.07
-0.05
-0.18
(0.03)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.04
-0.00
-0.05
-0.11
(0.04)
(0.02)
(0.03)
(0.04)
0.01
0.03
-0.02
-0.09
(0.03)
(0.02)
(0.02)
(0.03)
-0.02
0.03
-0.05
-0.14
(0.04)
(0.02)
(0.02)
(0.04)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.05
0.03
0.00
-0.10
(0.02)
(0.02)
(0.03)
(0.05)
0.06
-0.03
-0.10
-0.16
(0.02)
(0.02)
(0.02)
(0.04)
0.01
-0.01
-0.07
-0.10
(0.02)
(0.02)
(0.03)
(0.04)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
0.04 (0.04)
0.03 (0.02)
-0.01 (0.03)
0.06 (0.02)
0.01 (0.02)
-0.04 (0.02)
142
0.03 (0.03)
-0.00 (0.02)
0.01 (0.02)
LSPOOR
-0.13 (0.04)
-0.12 (0.03)
-0.08 (0.04)
PROXIES
PROXY
ANSPROXY
-0.05 (0.03)
-0.08 (0.04)
-0.13 (0.02)
0.00 (0.03)
-0.13 (0.02)
0.03 (0.03)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
R-SQUARE
0.07
0.13
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.34
-0.17
-0.02
0.01
0.04
0.06
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.36
-0.24
-0.03
0.03
0.06
0.06
(0.06)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
-0.31
-0.19
-0.04
0.02
0.03
0.05
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.02
-0.03
-0.04
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.01
0.05
-0.03
-0.03
-0.13
(0.02)
(0.02)
(0.02)
(0.03)
(0.03)
-0.02
0.02
-0.04
-0.05
-0.12
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.03
-0.02
-0.05
(0.03)
(0.01)
(0.01)
(0.02)
0.01
0.03
-0.06
-0.12
(0.06)
(0.03)
(0.02)
(0.03)
-0.04
0.00
-0.01
-0.04
(0.03)
(0.01)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.00
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
0.02
0.03
0.00
-0.10
(0.03)
(0.02)
(0.03)
(0.04)
0.04
-0.03
-0.08
-0.08
(0.01)
(0.01)
(0.02)
(0.02)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.02
0.01
-0.03
-0.08
(0.02)
(0.01)
(0.01)
(0.02)
0.03
0.05
-0.06
-0.19
(0.05)
(0.03)
(0.02)
(0.03)
0.02
0.01
-0.04
-0.15
(0.02)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
0.02 (0.02)
-0.07 (0.02)
0.01 (0.03)
143
-0.02 (0.01)
0.03 (0.02)
SINGLE REPORT OUTCOMES
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
R-SQUARE
0.08
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.39
-0.22
-0.03
0.03
0.05
0.07
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.38
-0.18
-0.04
0.02
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.04
-0.03
-0.03
-0.01
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.08
-0.04
0.01
0.04
0.01
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.04
-0.08
(0.01)
(0.00)
(0.00)
(0.01)
-0.13
-0.04
0.00
-0.01
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.00
-0.03
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.02
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.05
0.03
-0.04
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.03
-0.04
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.00)
0.03 (0.01)
0.02 (0.01)
0.05 (0.01)
144
Table A4d: 2003 Case-Mix Coefficients, Base Model Plus MHP, Plus Life Satisfaction, No Dual
Eligibles, No Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
R-SQUARE
Q46
Medicare
Q30
Health Care
Q7
Personal Dr
Q11
Specialist
0.08
0.07
0.04
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-1.17
-0.78
-0.44
0.34
0.52
0.61
(0.06)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.55
-0.07
-0.11
0.09
0.12
0.14
(0.05)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
0.11
0.17
-0.10
0.11
0.17
0.19
(0.05)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.23
0.11
-0.10
0.09
0.11
0.04
(0.06)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.08
0.16
-0.25
-0.39
-0.51
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.00
0.08
-0.17
-0.30
-0.35
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.09
0.13
-0.12
-0.25
-0.28
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
-0.01
0.08
-0.12
-0.24
-0.27
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.05
0.03
-0.04
(0.03)
(0.02)
(0.02)
(0.03)
0.16
0.07
-0.02
-0.07
(0.03)
(0.01)
(0.01)
(0.02)
0.02
0.01
0.05
0.10
(0.02)
(0.01)
(0.01)
(0.02)
0.03
0.01
0.01
-0.01
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.13
-0.09
-0.18
-0.27
(0.02)
(0.02)
(0.03)
(0.04)
0.18
-0.16
-0.25
-0.39
(0.01)
(0.01)
(0.02)
(0.04)
0.19
-0.13
-0.22
-0.25
(0.01)
(0.01)
(0.02)
(0.04)
0.20
-0.17
-0.27
-0.44
(0.02)
(0.02)
(0.03)
(0.05)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.38
0.19
-0.15
-0.23
(0.02)
(0.02)
(0.02)
(0.04)
0.42
0.22
-0.20
-0.39
(0.02)
(0.01)
(0.02)
(0.03)
0.38
0.17
-0.10
-0.19
(0.02)
(0.01)
(0.02)
(0.03)
0.36
0.17
-0.13
-0.28
(0.03)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.30 (0.02)
-0.03 (0.03)
-0.10 (0.02)
-0.04 (0.03)
-0.08 (0.02)
-0.08 (0.03)
-0.03 (0.02)
-0.04 (0.03)
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
R-SQUARE
AGE
AGE44
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
Q4
Problem
finding a
doctor/nurse
Q22
Problem with
delays in
health care
0.04
0.04
0.04
0.08
-0.24 (0.02)
-0.18 (0.01)
145
-0.15 (0.02)
-0.33 (0.04)
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.06
-0.01
0.01
-0.00
0.00
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.06
-0.01
0.00
-0.00
0.01
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.05
0.01
0.01
0.02
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.10
-0.02
0.05
0.05
0.06
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.01
-0.02
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
-0.01
-0.02
-0.02
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.00)
0.01
0.01
-0.05
-0.05
-0.08
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
-0.06
-0.01
-0.06
-0.07
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.02
-0.01
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.01
-0.01
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
0.02
0.02
-0.02
-0.04
(0.01)
(0.00)
(0.00)
(0.01)
0.01
-0.00
0.01
-0.03
(0.03)
(0.02)
(0.02)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.02
-0.06
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.01
-0.05
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
0.00
-0.02
-0.05
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.00
-0.00
-0.03
-0.15
(0.02)
(0.02)
(0.02)
(0.03)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.04
0.03
-0.04
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.03
-0.09
(0.01)
(0.00)
(0.00)
(0.01)
0.07
0.04
-0.04
-0.09
(0.01)
(0.00)
(0.01)
(0.01)
0.07
0.05
-0.03
-0.12
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.02 (0.01)
0.02 (0.00)
0.02 (0.01)
0.00 (0.01)
0.03 (0.01)
-0.04 (0.02)
0.01 (0.03)
GETTING CARE QUICKLY
R-SQUARE
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
0.05
0.05
0.04
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.21
-0.02
0.00
0.02
0.02
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.19
-0.04
-0.02
0.03
0.02
0.03
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.22
-0.02
-0.02
0.02
0.03
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.15
-0.01
-0.00
-0.01
-0.04
-0.03
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.01
0.02
-0.04
-0.08
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.02
-0.03
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
0.03
-0.05
-0.11
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
-0.01
-0.01
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
0.05 (0.01)
0.02 (0.01)
-0.01 (0.02)
0.01 (0.01)
146
0.07 (0.01)
0.03 (0.01)
0.16 (0.02)
0.07 (0.01)
FAIR
POOR
-0.01 (0.01)
-0.04 (0.01)
-0.02 (0.01)
-0.03 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.03 (0.01)
-0.04 (0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.05
-0.08
-0.11
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.04
-0.07
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.04
-0.08
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
0.04
-0.06
-0.06
-0.03
(0.01)
(0.01)
(0.01)
(0.02)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.12
0.07
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.02)
0.12
0.07
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.02)
0.14
0.07
-0.05
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
0.15
0.08
-0.06
-0.06
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.02 (0.01)
0.00 (0.01)
0.01 (0.01)
0.02 (0.02)
0.00 (0.01)
0.02 (0.01)
-0.03 (0.01)
0.10 (0.02)
DOCTOR COMMUNICATION
R-SQUARE
Q26
Provider
listen to you
Q27
Provider
explain things
Q28
Provider show
respect
Q29
Provider spend
enough time
0.04
0.05
0.04
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.11
-0.02
-0.02
0.01
0.02
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
0.06
0.00
-0.00
-0.01
-0.00
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.12
-0.00
-0.02
0.01
0.03
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.09
0.03
-0.01
0.01
0.01
0.03
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.04
0.05
-0.05
-0.08
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.02
0.03
-0.02
-0.06
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.03
-0.05
-0.06
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.05
-0.06
-0.11
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.01
-0.02
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
0.07
0.04
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.02
-0.01
-0.02
(0.01)
(0.01)
(0.01)
(0.01)
0.11
0.05
-0.02
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.04
-0.05
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
0.07
-0.05
-0.08
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.06
-0.04
-0.06
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
0.08
-0.05
-0.06
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.14
0.07
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.13
0.07
-0.06
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.12
0.07
-0.08
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.18
0.08
-0.09
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
-0.01 (0.01)
-0.05 (0.01)
147
-0.01 (0.01)
0.01 (0.01)
ANSPROXY
-0.02 (0.01)
-0.03 (0.01)
0.01 (0.01)
OFFICE STAFF
R-SQUARE
Q24
Office staff
courteous
Q25
Office staff
helpful
0.03
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.17
-0.04
-0.02
0.01
0.02
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.18
-0.03
-0.02
0.02
0.04
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
0.01
-0.03
-0.04
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.00
0.02
-0.05
-0.10
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.00
0.00
-0.00
-0.00
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.01
-0.01
-0.02
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
-0.03
-0.05
-0.06
(0.00)
(0.00)
(0.01)
(0.01)
0.05
-0.04
-0.06
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.07
0.03
-0.04
-0.08
(0.01)
(0.00)
(0.01)
(0.01)
0.12
0.06
-0.05
-0.09
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
0.00 (0.01)
-0.01 (0.01)
-0.01 (0.01)
-0.03 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
R-SQUARE
AGE
AGE44
AGE4564
AGE6569
AGE7579
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
Q41
Problem with
Medicare
paperwork
0.06
0.05
0.08
-0.06
-0.05
-0.06
0.02
(0.06)
(0.03)
(0.02)
(0.03)
-0.11
-0.05
-0.02
0.02
(0.05)
(0.02)
(0.02)
(0.02)
148
-0.03
0.00
0.01
0.07
(0.05)
(0.03)
(0.02)
(0.02)
-0.00 (0.01)
AGE8084
AGE85
0.04 (0.03)
0.08 (0.04)
0.03 (0.02)
0.08 (0.03)
0.08 (0.03)
0.10 (0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
0.03
-0.04
-0.07
-0.14
(0.04)
(0.03)
(0.02)
(0.03)
(0.03)
-0.11
-0.01
-0.03
-0.03
-0.08
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.04
-0.00
-0.08
-0.09
-0.17
(0.03)
(0.03)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
0.03
-0.02
-0.08
(0.04)
(0.03)
(0.02)
(0.03)
0.05
0.01
-0.02
-0.08
(0.03)
(0.02)
(0.02)
(0.03)
0.01
0.05
0.02
-0.03
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
-0.03
0.03
-0.03
0.05
(0.02)
(0.02)
(0.03)
(0.05)
0.01
-0.03
-0.12
-0.14
(0.02)
(0.02)
(0.02)
(0.04)
-0.03
-0.02
-0.10
-0.20
(0.02)
(0.02)
(0.03)
(0.04)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.07
0.06
-0.06
-0.19
(0.03)
(0.02)
(0.03)
(0.04)
0.12
0.07
-0.02
-0.05
(0.02)
(0.02)
(0.02)
(0.03)
0.06
0.03
-0.06
-0.10
(0.03)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.01 (0.03)
-0.04 (0.04)
-0.06 (0.02)
0.05 (0.03)
-0.14 (0.02)
0.03 (0.03)
SINGLE REPORT OUTCOMES
R-SQUARE
Q32
Getting
special
equipment
Q34
Getting home
health care
Q36
Getting
special
therapy
0.06
0.13
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.31
-0.16
-0.04
0.02
0.04
0.05
(0.03)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.36
-0.20
0.04
0.05
0.05
0.04
(0.06)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
-0.34
-0.17
-0.01
0.03
0.04
0.08
(0.04)
(0.02)
(0.01)
(0.01)
(0.01)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.01
-0.04
-0.05
-0.06
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
-0.04
-0.01
-0.06
-0.03
-0.17
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.04
0.00
-0.06
-0.03
-0.09
(0.02)
(0.01)
(0.01)
(0.02)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
-0.00
-0.01
-0.04
(0.03)
(0.02)
(0.01)
(0.01)
-0.15
-0.05
-0.03
-0.12
(0.07)
(0.03)
(0.02)
(0.03)
0.01
0.03
-0.02
-0.03
(0.03)
(0.01)
(0.01)
(0.02)
149
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
-0.00
-0.02
-0.03
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
0.03
-0.04
-0.10
-0.15
(0.03)
(0.02)
(0.02)
(0.03)
-0.00
-0.00
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.02)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.02
0.02
-0.03
-0.08
(0.02)
(0.01)
(0.01)
(0.02)
0.03
0.03
-0.06
-0.16
(0.04)
(0.02)
(0.02)
(0.03)
0.03
0.01
-0.04
-0.15
(0.02)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
0.02 (0.01)
-0.05 (0.02)
0.05 (0.02)
SINGLE REPORT OUTCOMES
R-SQUARE
Q38
Getting
prescription
medicines
Q39
How often get
prescription
medicine
0.08
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.47
-0.20
-0.04
0.03
0.04
0.06
(0.02)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.47
-0.18
-0.02
0.02
0.03
0.06
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.05
-0.02
-0.03
-0.03
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.08
-0.04
-0.02
-0.00
-0.02
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.03
0.02
-0.03
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.02
0.01
-0.02
-0.07
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.02
-0.06
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
0.01
-0.02
-0.07
-0.10
(0.00)
(0.00)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.05
0.03
-0.05
-0.08
(0.01)
(0.00)
(0.01)
(0.01)
0.04
0.03
-0.06
-0.10
(0.01)
(0.00)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.00 (0.01)
0.04 (0.01)
0.00 (0.01)
0.06 (0.01)
150
0.00 (0.01)
0.01 (0.02)
Table A4c_d: 2002 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, Plus Life Satisfaction, No Dual Eligibles, No Regional Interactions, Geo Unit
Reporting Entities
Q46
Medicare
Q30
Heakth Care
Q7
Personal Dr
Q11
Specialist
R-SQUARE
0.07
0.03
0.03
0.02
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.16
-0.08
-0.07
0.07
0.11
0.13
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.09
0.01
-0.03
0.03
0.03
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.01
0.04
-0.03
0.03
0.05
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
0.03
-0.02
0.02
0.01
-0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.05
0.07
-0.08
-0.16
-0.21
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.02
0.04
-0.03
-0.09
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.03
-0.09
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.00
0.01
-0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.02
-0.00
-0.00
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
-0.06
-0.01
0.01
0.02
(0.01)
(0.00)
(0.00)
(0.01)
-0.02
-0.00
0.01
0.04
(0.01)
(0.00)
(0.01)
(0.01)
-0.11
-0.05
0.04
0.07
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.07
-0.03
-0.04
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.03
-0.06
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.02
-0.04
-0.06
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.04
-0.06
-0.09
(0.00)
(0.00)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.13
0.03
-0.00
-0.02
(0.01)
(0.00)
(0.01)
(0.01)
0.10
0.03
-0.00
-0.02
(0.01)
(0.00)
(0.01)
(0.01)
0.11
0.03
-0.01
-0.02
(0.01)
(0.00)
(0.01)
(0.01)
0.05
0.01
0.01
-0.01
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.07 (0.01)
-0.04 (0.01)
-0.01 (0.01)
-0.06 (0.01)
151
0.01 (0.01)
-0.06 (0.01)
0.03 (0.00)
-0.04 (0.01)
Table A4d_d: 2003 Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base
Model Plus MHP, Plus Life Satisfaction, No Dual Eligibles, No Regional Interactions, Geo Unit
Reporting Entities
R-SQUARE
Q46
Medicare
Q30
Heakth Care
Q7
Personal Dr
Q11
Specialist
0.08
0.04
0.04
0.03
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.11
-0.09
-0.08
0.07
0.11
0.14
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.09
0.00
-0.04
0.02
0.03
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.02
0.03
-0.04
0.03
0.05
0.06
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.04
0.03
-0.03
0.02
0.01
-0.03
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.07
0.08
-0.08
-0.14
-0.18
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.00
0.02
-0.04
-0.09
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.03
-0.04
-0.10
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.01
0.01
-0.01
-0.00
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.04
0.01
0.02
0.02
(0.01)
(0.00)
(0.00)
(0.01)
-0.10
-0.03
0.04
0.05
(0.01)
(0.00)
(0.00)
(0.01)
-0.04
-0.02
0.03
0.06
(0.01)
(0.00)
(0.00)
(0.01)
-0.14
-0.06
0.06
0.10
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.07
-0.02
-0.02
-0.02
(0.00)
(0.00)
(0.01)
(0.01)
0.10
-0.05
-0.05
-0.09
(0.00)
(0.00)
(0.01)
(0.01)
0.09
-0.03
-0.05
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.04
-0.05
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.10
0.03
-0.01
-0.00
(0.01)
(0.00)
(0.01)
(0.01)
0.12
0.05
-0.02
-0.04
(0.01)
(0.00)
(0.01)
(0.01)
0.13
0.05
-0.01
-0.03
(0.01)
(0.00)
(0.01)
(0.01)
0.09
0.03
-0.01
-0.02
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.07 (0.01)
-0.04 (0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.00 (0.01)
-0.06 (0.01)
152
-0.01 (0.01)
-0.05 (0.01)
0.03 (0.00)
-0.05 (0.01)
Table A5e: Case-Mix Coefficients, Base Model Plus MHP, Plus Life Satisfaction, With Dual
Eligibles, No Regional Interactions, Geo Unit Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.07
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.91
-0.57
-0.36
0.33
0.53
0.64
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
-0.54
-0.15
-0.10
0.07
0.11
0.17
(0.04)
(0.02)
(0.01)
(0.02)
(0.02)
(0.02)
-0.01
0.14
-0.09
0.10
0.14
0.17
(0.04)
(0.02)
(0.01)
(0.01)
(0.02)
(0.02)
-0.51
-0.06
-0.11
0.05
0.06
0.11
(0.05)
(0.03)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.17
0.15
-0.21
-0.32
-0.46
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
0.07
0.12
-0.13
-0.25
-0.32
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.12
0.15
-0.10
-0.26
-0.28
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
0.07
0.10
-0.09
-0.19
-0.26
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.09
0.06
0.01
-0.01
(0.03)
(0.02)
(0.02)
(0.03)
0.15
0.07
-0.02
-0.09
(0.03)
(0.01)
(0.01)
(0.02)
0.03
0.00
0.03
0.07
(0.02)
(0.01)
(0.01)
(0.02)
-0.03
-0.00
0.00
0.01
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.11
-0.08
-0.11
-0.21
(0.02)
(0.02)
(0.02)
(0.04)
0.17
-0.11
-0.19
-0.29
(0.01)
(0.01)
(0.02)
(0.03)
0.17
-0.11
-0.15
-0.15
(0.01)
(0.01)
(0.02)
(0.03)
0.23
-0.12
-0.23
-0.30
(0.02)
(0.02)
(0.02)
(0.04)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.48
0.23
-0.19
-0.42
(0.02)
(0.02)
(0.02)
(0.04)
0.41
0.21
-0.19
-0.44
(0.02)
(0.01)
(0.02)
(0.03)
0.39
0.18
-0.10
-0.26
(0.02)
(0.01)
(0.02)
(0.03)
0.35
0.18
-0.14
-0.34
(0.03)
(0.02)
(0.02)
(0.04)
PROXIES
PROXY
ANSPROXY
-0.34 (0.02)
0.07 (0.03)
-0.14 (0.02)
-0.01 (0.02)
-0.09 (0.02)
-0.13 (0.02)
-0.11 (0.02)
-0.04 (0.03)
DUAL ELIG
0.68 (0.02)
0.02 (0.02)
0.07 (0.02)
0.00 (0.02)
153
0.04
COMPOSITE REPORT OUTCOMES
GETTING NEEDED CARE
Q9
Problem
seeing a
specialist
Q21
Problem
getting
necessary care
0.05
Q4
Problem
finding a
doctor/nurse
0.04
Q22
Problem with
delays in
health care
R-SQUARE
0.05
0.12
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.18
-0.07
-0.02
0.00
0.01
0.03
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.10
-0.04
-0.01
0.00
0.01
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.15
-0.07
0.00
0.00
0.02
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.31
-0.12
-0.05
0.02
0.04
0.08
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.00
-0.02
-0.03
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.00
-0.01
-0.02
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.03
0.03
-0.05
-0.04
-0.07
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
0.02
-0.01
-0.04
-0.07
-0.09
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.00
0.02
-0.02
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.01
-0.02
-0.06
(0.01)
(0.00)
(0.00)
(0.01)
0.02
0.01
-0.01
-0.05
(0.01)
(0.01)
(0.00)
(0.01)
0.05
0.00
-0.01
-0.05
(0.03)
(0.02)
(0.01)
(0.02)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.01
-0.01
-0.04
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
0.01
-0.01
-0.03
-0.08
(0.00)
(0.00)
(0.01)
(0.01)
-0.00
-0.01
-0.03
-0.06
(0.01)
(0.00)
(0.01)
(0.01)
-0.00
-0.01
-0.04
-0.09
(0.02)
(0.02)
(0.02)
(0.03)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.04
0.03
-0.04
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.03
-0.12
(0.01)
(0.00)
(0.00)
(0.01)
0.05
0.03
-0.05
-0.11
(0.01)
(0.00)
(0.01)
(0.01)
0.06
0.04
-0.03
-0.22
(0.02)
(0.02)
(0.02)
(0.03)
PROXIES
PROXY
ANSPROXY
0.02 (0.01)
0.01 (0.01)
0.01 (0.00)
0.00 (0.01)
0.01 (0.01)
0.03 (0.01)
-0.04 (0.02)
0.01 (0.03)
DUAL ELIG
-0.08 (0.01)
-0.07 (0.00)
-0.06 (0.01)
-0.11 (0.02)
GETTING CARE QUICKLY
Q14
Getting help
during
regular hrs.
Q18
Getting
immediate
care
154
Q16
Getting
regular health
care appt.
Q23
Waiting 15
minutes past
appt.
R-SQUARE
0.05
0.05
0.04
0.05
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.23
-0.05
-0.02
0.00
0.00
0.02
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.25
-0.08
-0.01
0.00
0.00
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.19
-0.04
-0.02
0.00
0.01
0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.17
-0.01
0.01
-0.02
-0.04
-0.05
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.02
0.02
-0.03
-0.07
-0.10
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.02
-0.03
-0.04
-0.07
-0.08
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.01
0.03
-0.05
-0.10
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.05
-0.00
0.00
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.03
-0.03
-0.05
(0.02)
(0.01)
(0.01)
(0.01)
0.04
0.02
-0.01
-0.02
(0.02)
(0.01)
(0.01)
(0.01)
0.10
0.04
-0.02
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
0.13
0.07
-0.04
-0.04
(0.02)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.05
-0.03
-0.06
-0.08
(0.01)
(0.01)
(0.01)
(0.02)
0.04
-0.02
-0.05
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
0.06
-0.03
-0.05
-0.10
(0.01)
(0.01)
(0.01)
(0.02)
0.04
-0.04
-0.06
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.12
0.06
-0.05
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.10
0.06
-0.05
-0.14
(0.01)
(0.01)
(0.01)
(0.02)
0.12
0.07
-0.06
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
0.13
0.07
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
PROXIES
PROXY
ANSPROXY
-0.04 (0.01)
0.03 (0.01)
0.00 (0.01)
0.06 (0.02)
-0.00 (0.01)
0.02 (0.01)
-0.05 (0.01)
0.08 (0.02)
DUAL ELIG
-0.05 (0.01)
-0.05 (0.01)
-0.02 (0.01)
-0.05 (0.01)
DOCTOR COMMUNICATION
Q26
Provider
listen to you
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
-0.14
-0.04
-0.02
-0.01
0.02
Q27
Provider
explain things
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.04
0.02
-0.01
-0.02
-0.02
Q28
Provider show
respect
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
155
-0.12
-0.02
-0.01
0.00
0.02
Q29
Provider spend
enough time
0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.13
-0.01
-0.01
-0.01
0.00
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
AGE85
0.04 (0.01)
-0.02 (0.01)
0.04 (0.01)
0.02 (0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.03
0.04
-0.06
-0.09
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.03
0.02
-0.02
-0.06
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.04
0.04
-0.04
-0.05
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
0.07
0.06
-0.05
-0.10
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.04
0.02
-0.02
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
0.07
0.03
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.05
0.02
-0.01
-0.04
(0.01)
(0.01)
(0.01)
(0.01)
0.09
0.04
-0.03
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.03
-0.04
-0.05
(0.01)
(0.01)
(0.01)
(0.01)
0.07
-0.04
-0.07
-0.11
(0.01)
(0.01)
(0.01)
(0.01)
0.06
-0.03
-0.06
-0.07
(0.01)
(0.01)
(0.01)
(0.01)
0.08
-0.03
-0.05
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.14
0.07
-0.05
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
0.14
0.08
-0.05
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.14
0.08
-0.06
-0.14
(0.01)
(0.01)
(0.01)
(0.01)
0.19
0.09
-0.07
-0.15
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.01 (0.01)
-0.01 (0.01)
-0.04 (0.01)
-0.03 (0.01)
-0.00 (0.01)
-0.00 (0.01)
-0.01 (0.01)
0.01 (0.01)
DUAL ELIG
0.00 (0.01)
0.01 (0.01)
0.00 (0.01)
0.01 (0.01)
OFFICE STAFF
Q24
Office staff
courteous
Q25
Office staff
helpful
R-SQUARE
0.04
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.17
-0.06
-0.02
0.00
0.02
0.04
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.18
-0.06
-0.02
0.01
0.03
0.04
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.02
-0.00
-0.02
-0.04
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.02
-0.05
-0.09
-0.12
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
156
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.01
-0.01
-0.00
-0.00
(0.01)
(0.00)
(0.00)
(0.01)
0.02
0.01
-0.01
-0.03
(0.01)
(0.01)
(0.01)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.03
-0.02
-0.04
-0.05
(0.00)
(0.00)
(0.01)
(0.01)
0.05
-0.03
-0.05
-0.06
(0.01)
(0.01)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.05
0.04
-0.03
-0.10
(0.01)
(0.00)
(0.00)
(0.01)
0.12
0.06
-0.05
-0.13
(0.01)
(0.01)
(0.01)
(0.01)
PROXIES
PROXY
ANSPROXY
0.00 (0.01)
-0.02 (0.01)
-0.02 (0.01)
-0.01 (0.01)
DUAL ELIG
-0.03 (0.01)
-0.03 (0.01)
CUSTOMER SERVICE, INFORMATION AND PAPERWORK
Q45
Getting help
from customer
service
Q43
Finding/
understanding
written info
R-SQUARE
0.04
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.08
-0.00
-0.04
0.00
0.05
0.01
(0.04)
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
0.09
0.04
-0.02
0.01
0.05
0.01
(0.03)
(0.02)
(0.02)
(0.02)
(0.02)
(0.02)
-0.06
-0.06
-0.03
-0.01
0.01
0.03
(0.04)
(0.02)
(0.02)
(0.02)
(0.02)
(0.03)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.03
-0.05
-0.07
-0.09
-0.12
(0.03)
(0.02)
(0.02)
(0.03)
(0.03)
-0.02
-0.03
0.00
0.01
0.03
(0.02)
(0.02)
(0.01)
(0.02)
(0.02)
-0.03
0.00
-0.05
-0.10
-0.09
(0.02)
(0.02)
(0.02)
(0.03)
(0.02)
GHP
EXCEL
VERYGOOD
FAIR
POOR
-0.02
-0.01
-0.03
-0.12
(0.04)
(0.02)
(0.02)
(0.03)
0.06
0.02
-0.05
-0.10
(0.03)
(0.02)
(0.01)
(0.02)
-0.05
-0.01
-0.01
-0.11
(0.04)
(0.02)
(0.02)
(0.03)
MHP
MHEXCEL
0.05
Q41
Problem with
Medicare
paperwork
0.00 (0.02)
0.08
0.05 (0.02)
157
0.03 (0.02)
MHGOOD
MHFAIR
MHPOOR
-0.01 (0.02)
-0.04 (0.03)
-0.08 (0.04)
-0.04 (0.01)
-0.09 (0.02)
-0.18 (0.03)
-0.00 (0.02)
-0.09 (0.02)
-0.09 (0.04)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.13
0.08
-0.00
-0.09
0.11
0.08
-0.05
-0.09
0.11
0.07
-0.03
-0.15
PROXIES
PROXY
ANSPROXY
-0.07 (0.02)
0.12 (0.04)
-0.11 (0.02)
0.10 (0.03)
-0.14 (0.02)
0.05 (0.03)
DUAL ELIG
0.05 (0.02)
0.07 (0.02)
0.01 (0.02)
(0.03)
(0.02)
(0.02)
(0.04)
(0.02)
(0.01)
(0.02)
(0.03)
(0.03)
(0.02)
(0.02)
(0.03)
SINGLE REPORT OUTCOMES
Q32
Getting
special
equipment
Q34
Getting home
health care
0.10
Q36
Getting
special
therapy
0.10
Q38
Getting
prescription
medicines
R-SQUARE
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.32
-0.14
-0.03
0.03
0.04
0.04
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
(0.01)
-0.34
-0.20
-0.03
0.01
0.04
0.02
(0.04)
(0.03)
(0.03)
(0.02)
(0.02)
(0.02)
-0.35
-0.19
-0.04
0.01
0.02
0.06
(0.03)
(0.02)
(0.01)
(0.01)
(0.01)
(0.01)
-0.28
-0.20
-0.03
0.03
0.05
0.08
(0.01)
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
-0.00
0.01
-0.03
-0.06
-0.11
(0.01)
(0.01)
(0.01)
(0.02)
(0.02)
-0.01
0.01
-0.07
-0.04
-0.15
(0.02)
(0.02)
(0.02)
(0.03)
(0.03)
0.00
0.00
-0.03
-0.07
-0.09
(0.02)
(0.01)
(0.01)
(0.02)
(0.01)
-0.03
-0.03
-0.02
-0.01
-0.04
(0.01)
(0.01)
(0.00)
(0.01)
(0.01)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.01
0.01
0.01
-0.05
(0.03)
(0.02)
(0.01)
(0.01)
-0.03
0.00
-0.04
-0.12
(0.06)
(0.03)
(0.02)
(0.02)
-0.02
-0.02
-0.02
-0.06
(0.03)
(0.01)
(0.01)
(0.01)
0.04
0.03
-0.05
-0.13
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.02
0.01
-0.02
-0.05
(0.01)
(0.01)
(0.01)
(0.02)
0.00
-0.01
-0.03
-0.15
(0.02)
(0.02)
(0.02)
(0.03)
0.01
-0.01
-0.06
-0.12
(0.01)
(0.01)
(0.01)
(0.02)
0.01
-0.00
-0.04
-0.07
(0.00)
(0.00)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
0.04 (0.02)
0.01 (0.01)
-0.05 (0.01)
0.09 (0.03)
0.07 (0.02)
-0.07 (0.02)
158
0.09
0.04 (0.02)
0.03 (0.01)
-0.02 (0.01)
0.04 (0.01)
0.03 (0.00)
-0.05 (0.01)
LSPOOR
-0.10 (0.02)
-0.10 (0.02)
-0.11 (0.02)
-0.12 (0.01)
PROXIES
PROXY
ANSPROXY
-0.03 (0.01)
0.03 (0.01)
-0.01 (0.02)
0.03 (0.02)
-0.04 (0.01)
0.03 (0.02)
-0.02 (0.01)
0.05 (0.01)
DUAL ELIG
-0.08 (0.01)
0.02 (0.02)
-0.03 (0.01)
-0.03 (0.01)
159
Table A5e_d: Case-Mix Coefficients for Global Ratings (Dichotomized 10 vs. 0-9), Base Model
Plus MHP, Plus Life Satisfaction, With Dual Eligibles, No Regional Interactions, Geo Unit
Reporting Entities
GLOBAL RATINGS
Q46
Medicare
Q30
Health Care
0.03
Q7
Personal Dr
0.03
Q11
Specialist
R-SQUARE
0.08
AGE
AGE44
AGE4564
AGE6569
AGE7579
AGE8084
AGE85
-0.12
-0.07
-0.07
0.07
0.11
0.14
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.09
-0.02
-0.04
0.02
0.02
0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.04
0.02
-0.03
0.03
0.04
0.05
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
-0.04
0.02
-0.03
0.02
0.01
-0.02
(0.01)
(0.01)
(0.00)
(0.00)
(0.00)
(0.01)
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
0.08
0.07
-0.07
-0.13
-0.17
(0.00)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.02
-0.03
-0.08
-0.11
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
0.01
0.04
-0.03
-0.10
-0.13
(0.01)
(0.00)
(0.00)
(0.01)
(0.01)
-0.03
-0.00
0.01
-0.00
-0.01
(0.00)
(0.00)
(0.00)
(0.01)
(0.00)
GHP
EXCEL
VERYGOOD
FAIR
POOR
0.06
0.02
0.01
0.03
(0.01)
(0.00)
(0.00)
(0.01)
-0.09
-0.03
0.04
0.06
(0.01)
(0.00)
(0.00)
(0.01)
-0.02
-0.02
0.03
0.06
(0.01)
(0.00)
(0.00)
(0.01)
-0.12
-0.06
0.06
0.10
(0.01)
(0.00)
(0.00)
(0.01)
MHP
MHEXCEL
MHGOOD
MHFAIR
MHPOOR
0.06
-0.01
-0.01
-0.00
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.04
-0.04
-0.05
(0.00)
(0.00)
(0.01)
(0.01)
0.08
-0.03
-0.03
-0.04
(0.00)
(0.00)
(0.01)
(0.01)
0.07
-0.04
-0.05
-0.06
(0.00)
(0.00)
(0.01)
(0.01)
LIFESAT
LSEXCEL
LSVERYGD
LSFAIR
LSPOOR
0.12
0.04
-0.02
-0.02
(0.01)
(0.00)
(0.00)
(0.01)
0.13
0.05
-0.02
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
0.13
0.05
-0.02
-0.05
(0.01)
(0.00)
(0.00)
(0.01)
0.08
0.03
-0.01
-0.03
(0.01)
(0.00)
(0.00)
(0.01)
PROXIES
PROXY
ANSPROXY
-0.08 (0.00)
-0.03 (0.01)
-0.02 (0.01)
-0.06 (0.01)
-0.01 (0.01)
-0.05 (0.01)
0.01 (0.00)
-0.04 (0.01)
DUAL ELIG
0.17 (0.00)
0.04 (0.00)
0.02 (0.00)
-0.00 (0.00)
160
0.03
APPENDIX B: CONSTRUCTION OF GEOGRAPHIC EQUIVALENCE WEIGHTS (GEWS)
In comparing MFFS and MA, there was concern that underlying geographic factors not
captured in a case-mix model might inappropriately influence MFFS-vs.-MA comparisons. In
order to ensure geographic equivalence of state-level comparisons, a team led by Alan Zaslavsky
at Harvard and Marc Elliott at RAND created county-based “geographic equivalence weights”
(GEW) in the “states” (including the District of Columbia and Puerto Rico) where MA exists.
The creation of GEW began with the creation of within-MFFS and within-MA weights.
Within MFFS, non-response weights were created by RTI to account for differential nonresponse within the MFFS sample, as described in the corresponding MFFS Task Report. These
weights were not particularly variable, with an average within-state design effect of
approximately 5%. Within MA, MA plans were weighted proportionately to their enrollments
within each state. The application of these weights within MFFS and MA resulted in somewhat
reduced precision but less biased representation of the experiences of the underlying populations.
An effective sample size (ESS), which downwardly adjusts from the nominal sample size to
account for this loss of precision, was calculated for MFFS and MA within each state.
County-level weights were then devised in order to be directly proportionate to the
harmonic mean of the MFFS and MA ESS’s, 1/(1/f + 1/m), where f and m are the MFFS ESS
and MA ESS, respectively. Thus, each county would have representation proportional to the
statistical “power” it could contribute to the state MFFS-vs.-MA comparison. This is a
compromise between matching to the MFFS distribution and matching to the MA distribution
which downweights counties that are sparse in either type of beneficiary.
2000 GEW
In four states (Maine, New Mexico, North Dakota, and West Virginia) application of
these county-level weights resulted in insufficient statistical power31 for comparison of MFFS
and MA, but similarly applied MFFS geo unit-level weights did provide sufficient statistical
power. Geo unit-level GEWs were used in those cases. In a further four states (Delaware,
Idaho, Nebraska, and New Hampshire), neither county-level nor geo unit-level GEWs allowed
sufficient statistical power, so no such equivalence weights were constructed.
2001 GEW
The targeted addition of 10,000 surveys to specific geo units in the eight states that did
not allow county-level matching in 2000, in combination with an increased MFFS response rate
in 2001, improved the specificity of 2001 GEWs and the resultant power for MFFS vs. MA
comparisons. Rather than four states with geo-unit-level matching and four with state-level
matching, five states fell into the first category (North Dakota, South Dakota, New Hampshire,
Nebraska, and Mississippi), and none fell into the least-desirable third category. 2001 MFFS
Subgroup Report findings (Bernard, Uhrig, et. al., 2002) that areas with higher MA penetration
31 According to a criterion of ESS of comparison t 225 that was selected to provide precision that is equivalent to
the typical precision of between-MA plan comparison.
161
had lower ratings and reports suggest that in the absence of the GEWs, the performance of MA
might have been underestimated relative to MFFS.
2002 GEW
The 2002 MFFS design relocated approximately 2300 surveys from the five states within
the best effective sample size for comparison to MA (California, Florida, New York,
Pennsylvania, and Ohio) to specific counties within geo units in the five states that did not permit
county-level GEWs. The weighting approach changed somewhat in that the new plan
comparison identifies plans (including MFFS) that are at or below the state mean. For this
reason, the effective sample size of the weighted MFFS “plan” became more important than the
effective sample size of the overall MFFS vs. MA state-level comparison. This year we selected
a threshold of 400 for the former, rather than a threshold of 22532 for the latter.
With this new criterion, nine states did not meet the threshold for county-level weighting:
Iowa, Kansas, Kentucky, New Mexico, North Dakota, Rhode Island, South Dakota, Virginia, and
West Virginia. This year we introduced a new first alternative when county-level matching was
not possible: equal weighting within geo units. When this also did not achieve the threshold,
geo-unit matching and state matching were tried in succession.
2003 GEW
The 2003 MFFS design benefits from advance notice of MA closures, and permitted a
county-level reallocation of 2175 surveys to better match the changing and in some cases very
localized MA presence within some states. The eight states that were identified as presenting
potential obstacles to county-level matching were Iowa, Kansas, Kentucky, New Mexico, North
Dakota, Rhode Island, Virginia, and West Virginia. Sample was transferred within geo units or
from geo units with at least 330 completes in the five states with the best ESS for comparison to
MA (Ohio, Pennsylvania, New York, California, and Florida). This advanced notice resulted in
by far the best precision to date, with all but two states meeting the threshold of 400 ESS for
county-level weighting: Idaho and Kentucky.
2004 GEW
The 2004 MFFS design benefits from advance notice of MA closures, and permitted a
county-level reallocation of 735 surveys to better match the changing and in some cases very
localized MA presence within some states. It appears that Idaho and Kentucky are the two states
that need more surveys in some counties. 105 surveys were reallocated within Idaho, and 620
surveys total were donated to Idaho and Kentucky from external sources: 300 from Puerto Rico
and 320 from geo units with at least 330 completes in the five states with the best ESS for
comparison to MA (Ohio, Pennsylvania, New York, California, and Florida). This resulted in all
states other than Puerto Rico meeting the threshold for county-level weighting, the best
performance to date.
2005 GEW
32 Equivalent to effective sample sizes of 450 for both MA and MFFS.
162
The 2005 MFFS design is not finalized at the time of this report, but the draft version does
benefit from information regarding changes in MA design and involves county-level reallocation
of 1055 surveys- 150 reallocations within state and 905 donations to New Hampshire, Iowa,
Kansas, West Virginia, and Puerto Rico from New York, Ohio, Pennsylvania, and Florida (the
four states with the highest remaining ESS for MA vs. MFFS comparisons). As before, donation
was restricted to geo units with at least 330 completes in the previous year.
163
APPENDIX C: NOTES ON CASE-MIX ADJUSTMENT OF THOSE UNDER AGE 65 (2000
DATA)
Note: This analysis has been summarized in a 2005 journal submission.
Do the effects of self-reported health differ for beneficiaries younger than 65?
Following up on a suggestion by 2001 MFFS TEP member Marsha Gold that the fivepoint measure of self-rated health (GHP) might behave differently for the disabled group under
age 65 than for others, we investigated whether CMA should allow different slopes for GHP in
this special group, using the four global ratings from the 2000 MFFS and MA. These analyses
were performed on the 2000 data that were used for MFFS vs. MA comparison- the 43 states
with MA, excluding the dually eligible33.
For reference, 7.6% of this MFFS sample and 6.4% of this MA sample is under 65 years
of age. On average, those under 65 rate their health approximately one unit lower than those 65
or over on the five-level GHP item. The median and modal GHP category is “GOOD” for those
65 and older and “FAIR” for those under 65. Among those 65 and over, 87.6% of MFFS and
86.7% of MA rate their health as “VERY GOOD,” “GOOD,” or “FAIR;” among those under 65,
94.7% of MFFS and 90.3% of MA rate their health as “GOOD,” “FAIR,” or “POOR.”
Although the pattern was stronger in MA than FFS, both showed a consistent "subadditivity" of poorer health and being under 65. In other words, being both younger than 65 and
in poorer health does not result in ratings as negative as the sum of the two effects independently
would suggest. This suggests that CMA that neglects this interaction may overcompensate plans
or FFS entities with high proportions of these "double vulnerables." In other words, although
those under 65 have markedly lower ratings and reports than the non-disabled, the slope of health
status on ratings and reports within the under 65 is less steep than in those 65 and over.
The first set of models described in Table C1a adds interaction terms between self-rated
health (GHP) dummies and an under 65 (AGE < 65) indicator. The highlighted coefficients
reflect the difference between the GHP coefficients for those under 65 and the corresponding
GHP coefficients for those 65 and over. The partial-F tests below assess the overall statistical
significance of these sets of four terms for each outcome against the null hypothesis that GHP
coefficients are the same for those over and under 65 years of age.
As can be seen in the first set of models, there is a trend for the interactions to increase
from negative for ‘AGE<65’xEXCELLENT to positive for ‘AGE<65’xPOOR for each of the
four global ratings for both MFFS and MA. This trend opposes the general pattern of increasing
ratings with higher GHP, and thus reflects a less steep slope for GHP among those under 65 than
those over 65. When tested as 4df (dummy) interactions, these differences are significant for
three of four MA measures and one of four MFFS measures. Because the trends are nearly linear
across levels of GHP, the dummy interactions are less efficient than a single degree of freedom
interaction of linear GHP with and ‘AGE<65’ dummy. The t-test of this term, unlike the partial
F test of the 4df parameterization, also considers the linear trend.
33
Dually eligibles are 8.5% of MFFS beneficiaries 65 and older, but 33% of MFFS beneficiaries under 65.
165
The second set of models uses the single degree of freedom (linear GHP x ‘AGE<65’)
interaction described above. This parameterization is significant at p=.05 (rounding) for three of
four global measures for both MFFS and MA. The magnitudes are such that the GHP slope is
only 1/3 to 2/3 as steep under 65 as over 65 among the three significant MA measures and only
5/9 to ¾ as steep under 65 as over 65 among the three significant MFFS measures.
Table C2a projects the coefficients for the dummy GHP version of Table C1a into
adjusted means, compared to a reference group of 70-74 year olds in “good” health, in order to
illustrate the magnitude of these effects. Adjustments are relative to this group within both
MFFS and MA individually. Figure C1 plots the entries from Table C2a.
Analyses by Paul Cleary and Alan Zavlavsky at Harvard suggest that there is little
variation in the proportion of beneficiaries under 65 from one MA plan to another, and hence
little effect of such an interaction on the relative case-mix adjustments to MA plans. These
proportions also do not vary much among MFFS geographical units. For these reasons, the
impact on CMA scores of such an approach would likely be small. Table 8b of the current report
formally analyzes the explanatory power of this parameterization within MFFS.
There are, however, other contexts in which CMA that considered age under 65 might
have a substantial impact, including reporting on the dual eligibles. Currently dual eligibles are
not included in MFFS vs. MA comparisons. Among the many reasons, the comparison focuses
on beneficiaries who have a choice between MA and MFFS in their geographic area, and this
does not apply to many dually eligible beneficiaries. If it were of interest, CMA-adjusted reports
comparing dually eligible MFFS and MA beneficiaries within CMA regions might be possible.
Second, these findings, and those that follow, may be helpful in parameterizing and interpreting
subgroup analyses.
Age effects under 65
It is well known that CAHPS scores increase strongly with respondent age across a wide
range of ages, as established in commercial settings. While the most salient characteristic of
Medicare beneficiaries under 65 may be the disability that resulted in early eligibility, this is also
he age category with the greatest variation in age among MFFS beneficiaries. In other words,
some of what has been interpreted as an effect of disability may actually be age-related response
tendencies, as noted in the 2000 MFFS CMA report.
Although the survey instrument did not specify any subdivisions of age under 65, it is
possible to construct subcategories using administrative DOB information. This information
unfortunately does not always agree with survey responses; following the precedent that has
been set, we gave the survey information priority in cases of disagreement. Here, we divide those
under 65 on the survey into subcategories of 18-39, 40-54, and 55-64, imputing the last category
for those few (2%) with DOBs indicating age over 64. By this definition 54% of beneficiaries
under 65 are 55-64, 39% are 40-54, and 7% are 18-39.
As can be seen in Table C1b, those 18-39 have much less favorable ratings than those 5564, with those 40-54 falling in between. Figure C2 plots the age trends, by comparing ratings to
the mean age within each subcategory across the full age range. The “Rate Medicare” item
166
appears to be linearly increasing in age, whereas the other three ratings appear to be linear in age
except for a downward displacement at 65 years of age. As can be seen in Table C2b, the ratings
of doctors and specialists by those 55-64 are very similar to the ratings of doctors and specialists
by those 70-74, but not similar to the ratings of doctors and specialists by those 18-54. The
ratings of health care and Medicare by those 55-64 are less favorable than similar ratings by
those 70-74, but they are still much more similar to the ratings of this older group than to the
ratings of those 18-54.
This pattern could be attributed to 1) pure age-related response patterns, 2) greater
disability in the youngest beneficiaries. The latter explanation is somewhat inconsistent with the
higher levels of self-rated health in the youngest age groups. As can be seen in Table C2b, only
22% of beneficiaries 55-64 rate their health as good or better, versus 25% of those 44-54 and
43% of those 18-39. Given that self-rated health is generally stable across age ranges, this does
not support the hypothesis of greater disability in the youngest group of beneficiaries.
Additionally, the rate of proxy responses is essentially identical for the three under 65 age
subgroups (26.5%, 26.6%, and 24.3% for 18-39, 40-54, and 55-64 respectively).
Finally, we can ask what happens when we consider age under 65 and the age<65 x GHP
interaction simultaneously. The second model in Table C1b examines this information for MFFS
(DOB information was not available on the joint file for MA). By comparing these results to the
first model in Table C1b, we can see that the interaction barely alters the pronounced age pattern
under 65. By comparing these results to the second model in Table C1a, we can observe that the
magnitude of the interaction is unchanged for the rating of the personal doctor, but is lessened
for the other three ratings.
Finally, it should be noted that, as with age under 65 by health status interactions, the
impact of age subcategories within the under 65 group on CMA is likely to be small. As detailed
in Table 8b of this report, the small variation in the proportion of beneficiaries under 65 across
units limits the impact of this variable on general CMA. On the other hand, this parameterization
adds very little survey burden and may assist in interpreting CMA and subgroup analyses reports
and may be useful in CMA of subgroups such as the under 65 population.
167
Table C1a: Differential Response of the Disabled Population (age < 65) on the GHP Item, CMA analysis, 2000, 43 States with MA,
Excluding Dual Eligibles
Variable
MA
FFS
Parameter P-value Parameter P-value Parameter P-value Parameter P-value Parameter P-value Parameter P-value Parameter P-value Parameter P-value
Estimate
Estimate
Estimate
Estimate
Estimate
Estimate
Estimate
Estimate
How would you
How would you
Rate overall
Rate all experience How would you
How would you
Rate overall
Rate all experience
rate your personal rate your specialist
healthcare
with health plan rate your personal rate your specialist
healthcare
with health plan
Doctor
Doctor
INTERACTION TERMS: AGE 64 BY GHP DUMMIES
Age < 65
-0.12 0.0017 *
-0.21 0.0000 *
-0.27 0.0000 *
-0.48 0.0000 *
0.03 0.5404
-0.12 0.0999
-0.34 0.0000 *
-0.91 0.0000 *
Age 65-69
-0.09 0.0000 *
-0.08 0.0000 *
-0.08 0.0000 *
-0.17 0.0000 *
-0.11 0.0000 *
-0.06 0.0121 *
-0.12 0.0000 *
-0.30 0.0000 *
Age 75-79
0.11 0.0000 *
0.07 0.0001 *
0.07 0.0000 *
0.15 0.0000 *
0.05 0.0009 *
0.06 0.0095 *
0.06 0.0001 *
0.18 0.0000 *
Age > 79
0.17 0.0000 *
0.07 0.0001 *
0.11 0.0000 *
0.23 0.0000 *
0.10 0.0000 *
0.07 0.0058 *
0.09 0.0000 *
0.32 0.0000 *
GHP: excellent
0.45 0.0000 *
0.37 0.0000 *
0.53 0.0000 *
0.58 0.0000 *
0.51 0.0000 *
0.29 0.0000 *
0.51 0.0000 *
0.37 0.0000 *
GHP: very good
0.20 0.0000 *
0.18 0.0000 *
0.26 0.0000 *
0.30 0.0000 *
0.20 0.0000 *
0.15 0.0000 *
0.23 0.0000 *
0.15 0.0000 *
GHP: fair
-0.18 0.0000 *
-0.21 0.0000 *
-0.26 0.0000 *
-0.26 0.0000 *
-0.10 0.0000 *
-0.12 0.0000 *
-0.17 0.0000 *
-0.07 0.0001 *
GHP: poor
-0.34 0.0000 *
-0.46 0.0000 *
-0.61 0.0000 *
-0.66 0.0000 *
-0.15 0.0000 *
-0.25 0.0000 *
-0.35 0.0000 *
-0.20 0.0000 *
(Age<65)*excellent
-0.06 0.5895
-0.15 0.3605
-0.14 0.2368
-0.11 0.3767
-0.14 0.4722
-0.18 0.6450
-0.02 0.9228
-0.56 0.0128 *
(Age<65)*very good
0.02 0.7564
-0.17 0.0980
0.03 0.7185
-0.10 0.2325
-0.15 0.1805
-0.10 0.5765
0.04 0.7647
0.03 0.8195
(Age<65)*fair
0.06 0.1974
0.11 0.0680
0.08 0.0674
-0.03 0.5028
-0.01 0.8133
-0.08 0.3393
0.04 0.4678
-0.03 0.6720
(Age<65)*poor
0.22 0.0001 *
0.29 0.0000 *
0.18 0.0004 *
0.04 0.5272
0.07 0.2974
0.02 0.7993
0.14 0.0222 *
0.08 0.2501
Partial F test
F-stat
P-value
F-stat
P-value
F-stat
P-value
4.69 0.0009 *
7.68 0.0000 *
4.25 0.0019 *
-0.32 0.0000 *
-0.09 0.0000 *
0.11 0.0000 *
0.17 0.0000 *
0.45 0.0000 *
0.20 0.0000 *
-0.18 0.0000 *
-0.33 0.0000 *
0.07 0.0002 *
-0.62 0.0000 *
-0.08 0.0000 *
0.07 0.0001 *
0.07 0.0001 *
0.38 0.0000 *
0.18 0.0000 *
-0.21 0.0000 *
-0.46 0.0000 *
0.13 0.0000 *
-0.46 0.0000 *
-0.08 0.0000 *
0.07 0.0000 *
0.11 0.0000 *
0.53 0.0000 *
0.26 0.0000 *
-0.26 0.0000 *
-0.60 0.0000 *
0.07 0.0001 *
F-stat
P-value
0.99 0.4109
F-stat
P-value
F-stat
1.37 0.2407
P-value
F-stat
P-value
F-stat
P-value
0.68 0.6062
1.6 0.1723
2.57 0.0362 *
-0.16 0.1082
-0.28 0.0755
-0.50 0.0000 *
-1.11 0.0000 *
-0.11 0.0000 *
-0.06 0.0121 *
-0.12 0.0000 *
-0.30 0.0000 *
0.05 0.0009 *
0.06 0.0092 *
0.06 0.0001 *
0.18 0.0000 *
0.10 0.0000 *
0.07 0.0056 *
0.09 0.0000 *
0.32 0.0000 *
0.51 0.0000 *
0.29 0.0000 *
0.51 0.0000 *
0.36 0.0000 *
0.19 0.0000 *
0.15 0.0000 *
0.23 0.0000 *
0.15 0.0000 *
-0.10 0.0000 *
-0.13 0.0000 *
-0.17 0.0000 *
-0.07 0.0000 *
-0.15 0.0000 *
-0.25 0.0000 *
-0.34 0.0000 *
-0.19 0.0000 *
0.05 0.0469 *
0.03 0.4444
0.05 0.0287 *
0.05 0.0548
INTERACTION TERMS: AGE 64 BY GHP LINEAR
Age < 65
Age 65-69
Age 75-79
Age > 79
GHP: excellent
GHP: very good
GHP: fair
GHP: poor
(Age<65)*GHP
-0.60 0.0000 *
-0.17 0.0000 *
0.15 0.0000 *
0.23 0.0000 *
0.58 0.0000 *
0.30 0.0000 *
-0.27 0.0000 *
-0.66 0.0000 *
0.03 0.1529
168
Note: The models also contain two dummy variables for proxy status and five for education as well as intercepts for geographical unit
(for the FFS sample) and plan (for the MA sample.)
169
Table Clb: Differential Response of the Disabled Population (age < 65) on the Health Survey
Item, CMA analysis with Additional Age Categories, Year 2000, 43 States with MA, No Dual
Eligibles
Parameter P-value
Parameter P-value
Estimate
Estimate
How would you rate
How would you rate
your personal Doctor
your specialist
FFS
Parameter P-value
Estimate
Rate overall healthcare
Parameter P-value
Estimate
Rate all experience
with health plan
ADDITIONAL AGE CATEGORIES: 18-39 AND 40-54
Age 18-39
-0.35
0.0001 *
-0.56
0.0000 *
-0.72
0.0000 *
-0.84 0.0000 *
Age 40-54
-0.21
0.0000 *
-0.25
0.0000 *
-0.36
0.0000 *
-0.55 0.0000 *
Age < 65
0.10
0.0020 *
-0.02
0.6770
-0.08
0.0076 *
-0.62 0.0000 *
Age 65-69
-0.14
0.0000 *
-0.06
0.0115 *
-0.12
0.0000 *
-0.30 0.0000 *
Age 75-79
0.07
0.0000 *
0.06
0.0223 *
0.06
0.0001 *
0.18 0.0000 *
Age > 79
0.11
0.0000 *
0.06
0.0228 *
0.08
0.0000 *
0.31 0.0000 *
GHP: excellent
GHP: very
good
0.39
0.0000 *
0.27
0.0000 *
0.50
0.0000 *
0.36 0.0000 *
0.17
0.0000 *
0.15
0.0000 *
0.23
0.0000 *
0.15 0.0000 *
GHP: fair
-0.08
0.0000 *
-0.13
0.0000 *
-0.17
0.0000 *
-0.07 0.0000 *
GHP: poor
-0.11
0.0000 *
Age 18-39
-0.33
0.0002 *
-0.55
0.0000 *
-0.71
0.0000 *
-0.84 0.0000 *
Age 40-54
-0.21
0.0000 *
-0.25
0.0000 *
-0.36
0.0000 *
-0.55 0.0000 *
Age < 65
-0.12
0.2643
-0.08
0.5964
-0.22
0.0393 *
-0.69 0.0000 *
Age 65-69
-0.14
0.0000 *
-0.06
0.0114 *
-0.12
0.0000 *
-0.30 0.0000 *
Age 75-79
0.07
0.0000 *
0.06
0.0221 *
0.06
0.0001 *
0.18 0.0000 *
Age > 79
0.11
0.0000 *
0.06
0.0223 *
0.08
0.0000 *
0.31 0.0000 *
GHP: excellent
GHP: very
good
0.39
0.0000 *
0.27
0.0000 *
0.50
0.0000 *
0.36 0.0000 *
-0.26 0.0000 *
-0.34
0.0000 *
ADDITIONAL AGE CATEGORIES: 18-39 AND 40-54;
INTERACTION TERM: AGE 64 BY GHP (linear)
-0.20 0.0000 *
0.17
0.0000 *
0.15
0.0000 *
0.23
0.0000 *
0.15 0.0000 *
GHP: fair
-0.08
0.0000 *
-0.14
0.0000 *
-0.18
0.0000 *
-0.08 0.0000 *
GHP: poor
-0.13
0.0000 *
-0.26
0.0000 *
-0.35
0.0000 *
-0.20 0.0000 *
0.05
0.0335 *
0.02
0.6659
0.03
0.1763
0.02 0.5626
(Age<65)*GHP
Note: The models also contain two dummy variables for proxy status and five for education as
well as intercepts for geographical unit.
170
Table C2a: 2000 Comparison of Global Ratings by those under 65 to those 70-74 and in Good Health
AGE
Age < 65
HEALTH
STATUS
MA
How would
you rate your
specialist
Rate overall
healthcare
Rate all
experience
with health
plan
Good
23.41
Fair
43.18
0.26
0.10
-0.12
-0.24
Poor
23.72
-0.25
-0.39
-0.69
-1.10
Excellent
2.76
Very Good
6.92
0.01
-0.21
-0.21
-0.31
0.12
0.02
-0.27
-0.45
0.00
-0.27
-0.48
-0.77
Percent in
FFS Sample
How would
you rate your
personal
Doctor
FFS
How would
you rate your
specialist
Rate overall
healthcare
Rate all
experience
with health
plan
1.16
0.40
-0.02
0.15
4.16
0.08
-0.07
-0.08
-1.10
-0.73
20.27
0.03
-0.12
-0.34
-0.91
42.01
-0.08
-0.33
-0.47
-1.00
32.41
-0.05
-0.36
-0.54
-1.02
8.17
0.45
0.37
0.53
0.58
7.81
0.51
0.29
0.51
0.37
Very Good
25.63
0.23
0.15
20.99
0.30
0.00
-0.26
0.15
41.36
0.26
0.00
-0.26
0.20
Fair
0.18
0.00
-0.21
27.00
Good
0.20
0.00
-0.18
Poor
3.85
-0.34
-0.46
-0.61
-0.66
Excellent
Age70-74
How would
you rate your
personal
Percent in MA
Doctor
Sample
38.55
0.00
0.00
0.00
0.00
21.71
-0.10
-0.12
-0.17
-0.07
4.93
-0.15
-0.25
-0.35
-0.20
Note: This table is based on results presented in the upper portion of Table C1a with dummy coded GHP and ‘age<65’ interaction
terms. Each cell in the table represents the sum of the coefficients of relevant age, health status, and their interaction dummy
variables. The reference point is within survey type, MA or FFS.
171
Table C2b. 2000 Comparison of Global Ratings by three age categories under age 65 to those
70-74 and in Good Health (model includes GHP by ‘Age<65’ interaction)
How would
you rate your
personal
Doctor
AGE
Age 18-39
Excellent
4.46
0.00
-0.35
-0.39
-1.15
Very Good
9.15
-0.17
-0.46
-0.63
-1.34
Good
29.34
-0.28
-0.59
-0.82
-1.47
Fair
37.79
-0.31
-0.71
-0.97
-1.53
Poor
19.25
-0.31
-0.82
-1.11
-1.64
0.80
0.12
-0.04
-0.04
-0.86
4.17
-0.05
-0.15
-0.28
-1.06
Good
19.74
-0.17
-0.28
-0.47
-1.19
Fair
41.89
-0.20
-0.40
-0.61
-1.24
Poor
33.39
-0.19
-0.52
-0.76
-1.36
Excellent
0.84
0.33
0.21
0.32
-0.31
Very Good
3.22
0.16
0.09
0.08
-0.51
17.82
0.04
-0.04
-0.11
-0.64
Good
Fair
43.43
0.02
-0.15
-0.26
-0.70
Poor
34.69
0.02
-0.27
-0.40
-0.81
Excellent
Age70-74
Rate all
experience
with health
plan
Percent in
FFS Sample
Very Good
Age 55-64
Rate overall
healthcare
HEALTH
STATUS
Excellent
Age 40-54
FFS
How would
you rate your
specialist
7.84
0.39
0.27
0.50
0.36
Very Good
27.11
0.17
0.15
0.23
0.15
Good
38.32
0.00
0.00
0.00
0.00
Fair
21.68
-0.08
-0.14
-0.18
-0.08
Poor
5.06
-0.13
-0.26
-0.35
-0.20
Note: This table is based on results presented in Table C1b labeled ‘ADDITIONAL AGE
CATEGORIES: 18-39 AND 40-54; INTERACTION TERM: AGE 64 BY GHP (linear)’. Each
cell in the table represents the sum of the coefficients of relevant age and health status categories.
172
Figure C1: 2000 Comparison of Global Ratings by those under 65 to those 70-74 and in Good
Health
MA
FFS
173
Note: Results based on Table C2a.
174
Figure C2: 2000 illustration of linear pattern in age among beneficiaries under 65, 43 States with
MA, no dual eligibles
Note: This is a comparison of various age categories to age 70-74 and in Good Health.
Here the ‘good health’ category of GHP is plotted. The regression model includes GHP by
’Age<65’ interaction in addition to two dummy variables for proxy status and five for education
as well as intercepts for geographical units. This figure is based on results presented in Tables
C1b and Q2b.
175
APPENDIX D: EXPLORATORY ANALYSIS OF CURRENT LIFE SATISFACTION ITEM
ON 2002 AND 2003 MFFS SURVEYS
Purpose
A new item asking respondents to rate their overall current life satisfaction (CLS) as
being “poor,” “fair,” “good,” “very good,” or “excellent” was added to the 2002 MFFS survey
but not the 2002 MA survey. This item was designed to enhance the Case-Mix Adjustment
(CMA) model, both for adjustment within MFFS and ultimately (if added to the MA survey),
MFFS vs. MA CMA.
The Non-Empirical Case For CLS
One desirable property about this CLS item is that, on the face of it, it attempts to directly
measure response bias/response tendencies, rather than measuring such tendencies indirectly
through demographic variables and health status measures, which may measure a combination of
both response tendencies and actual differences in care (see Elliott, Swartz, et. al., 2001) for an
extended treatment of this argument). Because of this property, this CLS measure may be
“cleaner” and more defensible than other adjusters of equal empirical power. It should also be
noted that the current GHP item is the one current CMA adjuster with the undesirable property of
substantially different slopes for MFFS and MA, at least for global ratings, although this
tendency may be diminishing over time. If CLS did not have this property (which could only be
assessed after inclusion of CLS on the MA survey), it might better allow us to separate the casemix adjustment and subgroup analysis aspects of the GHP by MFFS/MA interactions. In other
words, it might make it clearer whether GHP as health status, controlling for response
tendencies, truly interacts with the MFFS/MA distinction.
The Non-Empirical Case Against CLS
Some have argued that the nature of the CLS item might result in some criticism of
CAHPS and CMS by interested third parties unfamiliar with case-mix adjustment of selfreported survey data. Case-mix adjustment of survey data resembles the more familiar case-mix
adjustment of outcomes data in that it attempts to correct for differences in patient characteristics
that contribute to outcomes in ways that beyond the control of the providers being compared.
When medical outcomes are the outcomes in question, one usually adjusts for factors such as
severity of illness that directly contribute to poorer outcomes. In the case of self-reported survey
data, it is systematic response tendencies on the part of respondents that similarly contribute to
poorer evaluations. While CMA for self-reported data is no less valid or useful than CMA for
traditional medical outcomes, some feel that the use of items such as CLS, which more clearly
measure response tendencies than do variables such as self-rated health or education, may fuel
perception of CAHPS data as subjective and unreliable among those already skeptical of selfreported data.
Empirical Assessment of CLS
The rest of this memo address the empirical properties of the CLS item in 2002 MFFS
data. First, the item has a fairly symmetric, unimodal distribution without ceiling or floor effects:
12% excellent, 30% very good, 32% good, 20% fair, and 6% poor. It most strongly correlates
176
with self-rated general health (GHP), at r=+0.77, followed by a correlation of r=+0.65 with selfrated mental health (MHP). All other correlations with case-mix adjusters in the current model
(education, age, proxy status) are below 0.3 in absolute value. For comparison the highest
correlation among current CMA variables is r=+0.66 between GHP and MHP. It appears that
most of the correlation of MHP, education, age, and proxy status with CLS is through their
correlations with GHP, since the multiple correlation of all current case-mix adjusters with CLS
is r=+0.79.
When CLS is added to current CMA models for the four global ratings, it takes on large
and statistically significant positive coefficients in all cases (higher life satisfaction associated
with better care). The coefficients of MHP, education, age, and proxy status are affected very
little, but the effects of GHP are substantially attenuated, becoming essentially negligible. The
“spacing” of dummy coefficients is very nearly linear (each unit of CLS has an equal effect of
outcomes).
2003 Update
Exploratory 2003 analyses looked for demographic or other characteristics
strongly correlated with CLS in order to assess the potential for CLS to clarify subgroup patterns.
No especially strong patterns of this time were found. This implies that the primary value of
CLS would be as a case-mix adjustor. Empirically, it would probably be about the third most
important CMA if implement.
2004 Update
Table D.1 looks as subgroup patterns in a series of three models. Subgroups are
defined by all recommended CMA variables, plus race/ethnicity. Model 1 display bivariate
patterns, after adjusting for geo unit dummies. Model 2 adjusts for all recommended CMA
variables. Model 3 adds the CLS item to Model 2. The only subgroup comparison that would be
substantially impacted by the CLS item would be the comparison of groups by overall self-rated
health status. The CLS item would result in considerably smaller differences in global ratings by
general health status.
177
Table D1. Multiple Regressions Examining the Impact of Current Life Satisfaction on Subgroup Comparisons
How do you rate your
personal doctor or
nurse?
Model
1
Model
2
How do you rate your
specialist?
Model
3
Model
1
0.20*
(0)
-0.17*
-0.26*
-0.36*
0.25*
(0)
-0.23*
-0.42*
-0.66*
Model
2
Model
3
How do you rate all
your experience with
your health care?
Model
1
Model
2
How do you rate your
experience with
Medicare?
Model
3
Model
1
0.19*
(0)
-0.21*
-0.39*
-0.62*
0.16*
(0)
-0.2*
-0.4*
-0.67*
Model
2
Model
3
Life Satisfaction
Excellent
Very Good
Good
Fair
Poor
0.25*
(0)
-0.19*
-0.27*
-0.4*
0.19*
(0)
-0.16*
-0.29*
-0.4*
Excellent
Very Good
Good
Fair
Poor
0.29*
0.14*
(0)
-0.05*
-0.12*
0.16*
0.07*
(0)
-0.01
-0.01
0.04
0.01
(0)
0.05*
0.1*
0.32*
0.16*
(0)
-0.15*
-0.35*
0.16*
0.07*
(0)
-0.06*
-0.15*
Excellent
Very Good
Fair
Poor
0.39*
0.15*
-0.09*
-0.21*
0.41*
0.17*
-0.1*
-0.2*
0.31*
0.12*
-0.06*
-0.13*
0.48*
0.23*
-0.16*
-0.48*
0.46*
0.21*
-0.12*
-0.37*
<8th grade
-0.01
Some high school 0.08*
High school
(0)
Graduate/GED
Some college
-0.07*
College graduate –0.16*
More than 4 year –0.17*
college
0.08*
0.12*
(0)
0.08*
0.12*
(0)
-0.11*
-0.23*
-0.26*
-0.12*
-0.24*
-0.29*
0.28*
(0)
-0.31*
-0.6*
-0.98*
0.18*
(0)
-0.2*
-0.33*
-0.45*
GHP
0.06
0.02
(0)
0.01
-0.01
0.45*
0.23*
(0)
-0.23*
-0.53*
0.3*
0.14*
(0)
-0.12*
-0.27*
0.17*
0.07*
(0)
-0.03*
-0.07*
0.19*
0.12*
(0)
-0.11*
-0.39*
0.19*
0.12*
(0)
-0.06*
-0.19*
0.07*
0.06*
(0)
0.02
-0.05+
0.53*
0.27*
-0.24*
-0.63*
0.45*
0.22*
-0.12*
-0.38*
0.33*
0.16*
-0.06*
-0.24*
0.26*
0.14*
-0.18*
-0.47*
0.32*
0.14*
-0.08*
-0.24*
0.2*
0.09*
-0.04+
-0.15*
0.01
0.07*
(0)
0.01
0.08*
(0)
0.12*
0.16*
(0)
0.09*
0.17*
(0)
0.09*
0.17*
(0)
-0.17*
-0.28*
-0.32*
-0.18*
-0.29*
-0.35*
-0.25*
-0.28*
-0.39*
-0.25*
-0.37*
-0.49*
-0.26*
-0.39*
-0.52*
MHP
0.36*
0.17*
-0.07*
-0.29*
Education
-0.13*
0.02
(0)
-0.06*
-0.12*
-0.1*
0.00
0.08*
(0)
0.01
0.09*
(0)
-0.11*
-0.22*
-0.25*
-0.11*
-0.24*
-0.27*
x
x
continued –
178
-0.16*
-0.02
(0)
-0.12*
-0.14*
-0.13*
Age
< 44
45 65 70 75 80 > 85
-0.24*
-0.02
-0.07*
(0)
0.06*
0.09*
0.04*
-0.11*
0.11*
-0.09*
(0)
0.09*
0.15*
0.16*
-0.07+
0.15*
-0.09*
(0)
0.1*
0.16*
0.17*
-0.59*
-0.21*
-0.08*
(0)
0.02
0.01
-0.11*
0.03+
0.1*
0.11*
-0.16*
0.01
No Assistance
Assistance
Respond
(0)
-0.1*
-0.17*
(0)
-0.11*
-0.11*
(0)
-0.11*
-0.1*
(0)
-0.14*
-0.14*
(0)
-0.06*
-0.06+
White
Hispanic
Black
Asian
American Native
Other race
(0)
0.16*
0.11*
-0.25*
-0.06
0.07
(0)
0.18*
0.14*
-0.17*
-0.01
0.1
(0)
0.18*
0.13*
-0.16*
-0.02
0.09
(0)
-0.08*
-0.13*
-0.5*
-0.2*
-0.12
64
69
74
79
84
-0.35*
0.02
-0.1*
(0)
0.06*
0.09*
0.03
-0.31*
0.06*
-0.1*
(0)
0.07*
0.09*
0.05+
-0.99*
-0.45*
-0.08*
(0)
0.02
0.01
-0.08*
-0.69*
-0.14*
-0.11*
(0)
0.07*
0.11*
0.12*
-0.63*
-0.09*
-0.11*
(0)
0.08*
0.12*
0.13*
-0.93*
-0.78*
-0.4*
(0)
0.27*
0.4*
0.39*
-0.98*
-0.71*
-0.42*
(0)
0.3*
0.47*
0.54*
-0.94*
-0.67*
-0.42*
(0)
0.31*
0.48*
0.55*
-0.27*
-0.01
0.01
0.3*
0.59*
0.61*
(0)
-0.23*
-0.16*
(0)
-0.13*
-0.09*
(0)
-0.12*
-0.07*
(0)
-0.16*
-0.05+
(0)
-0.33*
-0.06*
(0)
-0.33*
-0.05
(0)
-0.1*
-0.17*
-0.4*
-0.38*
-0.31*
(0)
0.05+
-0.02
-0.25*
-0.22*
-0.18+
(0)
0.05+
-0.03
-0.25*
-0.22*
-0.19+
(0)
0.25*
0.03
0.03
-0.37*
-0.01
(0)
0.29*
0.11*
0.04
-0.19*
0.08
(0)
0.29*
0.1*
0.05
-0.19*
0.07
DuAl Eligibility
Indicator
0.03
Proxy
(0)
-0.05*
-0.04
Race/Ethnicity
(0)
0.01
-0.04
-0.4*
-0.11+
-0.06
(0)
0.00
-0.05+
-0.39*
-0.12*
-0.08
* p < 0.05. + p < 0.10.
Model 1. Bivariate linear regression analyses adjusting for geographical units were performed for each predictor
category.
Model 2. Multivariate linear regression analysis adjusting for geographical units was performed using all predictors
with the exception of ‘life satisfaction’ and ‘race/ethnicity.’ The reported coefficients and p-values for the
‘race/ethnicity’ category are based on a model that additionally included ‘race/ethnicity.’
Model 3. Multivariate linear regression analysis adjusting for geographical units was performed using all predictors
with the exception of ‘race/ethnicity.’ The reported coefficients and p-values for the ‘race/ethnicity’ category are
based on a model that additionally included ‘race/ethnicity.’
179
APPENDIX E: SUPPLEMENTARY TABLES FROM EARLIER REPORTING YEARS
Table E1a: Comparison of Magnitude of CMA Coefficients, FFS vs. MA (2000)
Standard Deviation of Outcome per Level of Ordinal Adjustor
AGE
EDUCATION
General Health
(5 levels)
(6 levels)
(5 levels)
FFS
MA
FFS
MA
FFS
MA
GLOBAL (scale 0=worst - 10=best)
How would you rate your personal Doctor
How would you rate your specialist
Rate overall healthcare
Rate all experience with health plan
0.03
0.03
0.05
0.13
0.05 *
0.03
0.05
0.08 *
-0.05
-0.04
-0.05
-0.07
0.07
0.04
0.02
0.03
0.06
0.04
0.03
0.05 *
-0.05
-0.01
-0.01
0.00
0.10
0.07
0.05
0.06
0.06
0.08
-0.09
-0.03
-0.06
0.02
0.03
0.04
0.01
0.03
0.04
0.04
0.02
0.02
-0.01
0.03
0.01
0.03
0.00
0.04
0.02
-0.06
-0.05
-0.07 *
-0.08
-0.08
-0.08
-0.13
-0.08
-0.11 *
-0.11 *
-0.17 *
-0.16 *
-0.08
-0.10
-0.10
-0.04
-0.11
-0.08
-0.13 *
-0.14 *
-0.07
-0.02
-0.09 *
-0.04
-0.07
-0.08
-0.08
-0.10
-0.08
-0.04
-0.04
-0.02
-0.02
-0.03
-0.05
-0.02
-0.02
-0.10
-0.08
-0.09
-0.13
-0.12
-0.11 *
-0.11
-0.13
-0.05
-0.02
-0.03
-0.04
-0.05
-0.02
-0.04
-0.05
-0.12
-0.14
-0.13
-0.14
-0.14 *
-0.16
-0.15
-0.16 *
GETTING NEEDED CARE (scale 1-4)
Was it a problem getting your choice of Doctor
Problem getting referral to specialist
Problem getting care needed
Problem waiting for plan approval
CONSUMER SERVICE, INFORMATION,
AND PAPERWORK (scale 1-4)
Customer service, problem getting help
Problem understanding materials
Paperwork problems
-0.06
-0.03
-0.02
-0.04 *
GETTING CARE QUICKLY (scale 1-5)
Got help/advice needed
For routine care, saw Doctor wanted
Got care as soon as wanted
a
How often waited more than 15 minutes
DOCTOR COMMUNICATION (scale 1-5)
Doctor listened carefully
Doctor explained well
Doctor showed respect to you
Doctor spent enough time with you
a
The scale for this variable has been reversed so that 1=Always and 4=Never (5=No visit)
|MA Coefficient| > |FFS Coefficient|, p < 0.05
|FFS Coefficient| > |MA Coefficient|, p < 0.05
180
Table E1b: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2001)
AGE
(6 levels)
FFS
MA
STANDARDIZED COEFFICIENTS
EDUCATION
GHP
(6 levels)
FFS
MA
(5 levels)
FFS
MHP
(5 levels)
MA
FFS
MA
GLOBAL (scale 0=worst - 10=best)
How would you rate your personal Dr. now
How would you rate your spec. now
6 mo, rate overall healthcare
Rate all experience with health plan
0.02
0.02
0.03
0.11
0.04 *
0.01
0.04
0.08 *
-0.06
-0.05
-0.07
-0.08
-0.07
-0.06
-0.08
-0.09
-0.03
-0.05
-0.09
-0.05
-0.07 *
-0.05
-0.12 *
-0.12 *
-0.08
-0.11
-0.12
-0.08
-0.08
-0.10
-0.11
-0.08
0.02
0.02
0.01
0.03
0.04 *
0.03
0.03
0.05 *
-0.03
-0.01
-0.02
0.00
-0.07 *
-0.03 *
-0.03 *
-0.04 *
-0.07
-0.07
-0.08
-0.03
-0.12 *
-0.08
-0.10
-0.11 *
-0.04
-0.06
-0.05
-0.04
-0.04
-0.04
-0.07
-0.06
0.05
0.05
0.04
0.05
0.04
0.09 *
-0.06
-0.02
-0.04
-0.07
-0.01
-0.11 *
-0.03
-0.05
-0.07
-0.07
-0.07
-0.06
-0.05
-0.09
-0.05
-0.03
-0.07
-0.02
0.01
0.02
0.02
0.01
0.02
0.03
0.03
0.02
-0.04
-0.04
-0.03
-0.02
-0.04
-0.04
-0.04
-0.02
-0.08
-0.05
-0.06
-0.12
-0.09
-0.08 *
-0.08
-0.12
-0.08
-0.07
-0.08
-0.03
-0.08
-0.08
-0.08
-0.03
0.01
-0.02
0.02
0.00
0.03
-0.01
0.03
0.01
-0.06
-0.03
-0.04
-0.06
-0.06
-0.03
-0.05
-0.06
-0.08
-0.09
-0.09
-0.10
-0.10
-0.11 *
-0.11
-0.12
-0.09
-0.10
-0.10
-0.08
-0.09
-0.11
-0.09
-0.09
GETTING NEEDED CARE (scale 1-4)
Was it a prob getting your choice of Dr.
6 mo: prob getting referral to spec.
6 mo; prob getting care needed
6 mo; prob waiting for plan approval
CONSUMER SERVICE, INFORMATION,
AND PAPERWORK (scale 1-4)
6 mo, customer serv, prob getting help
6 mo, prob understanding materials
6 mo, Paperwork probs
GETTING CARE QUICKLY (scale 1-5)
6 mo; got help/advice needed
6 mo; for routine care, saw Dr wanted
6 mo; got care as soon as wanted
a
6 mo; how often waited > 15 mins
DOCTOR COMMUNICATION (scale 1-5)
6 mo, Dr. listened carefully
6 mo, Dr. explained well
6 mo, Dr. showed respect to you
6 mo, Dr. spent enough time with you
if |MA beta| > |ffs beta|
if |ffs beta| > |MA beta|
a
The scale for this variable has been reversed so that 1=Always and 4=Never (5=No visit)
181
Table E1c: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2002)
STANDARDIZED COEFFICIENTS
AGE
EDUCATION
GHP
MHP
(7 levels)
(6 levels)
(5 levels)
(5 levels)
FFS MA
FFS MA
FFS MA
FFS MA
0.02
0.02
0.04
0.14
0.04 *
0.03
0.04
0.09 *
-0.05
-0.04
-0.06
-0.07
-0.06
-0.05
-0.07
-0.07
-0.04
-0.06
-0.10
-0.06
-0.07 *
-0.05
-0.12 *
-0.12 *
-0.09
-0.11
-0.12
-0.09
-0.08
-0.11
-0.11
-0.08
0.02
0.03
0.03
0.08
0.04
0.04
0.04
0.07
-0.03
-0.00
-0.00
-0.04
-0.06 *
-0.03 *
-0.02
-0.05
-0.07
-0.07
-0.07
-0.07
-0.12 *
-0.09
-0.10
-0.09
-0.05
-0.06
-0.06
-0.07
-0.03
-0.06
-0.06
-0.05
GLOBAL (scale 0=worst - 10=best)
How would you rate your personal Dr. now
How would you rate your spec. now
6 mo, rate overall healthcare
Rate all experience with health plan
GETTING NEEDED CARE (scale 1-4)
Was it a prob getting your choice of Dr.
6 mo: prob getting referral to spec.
6 mo; prob getting care needed
6 mo; prob waiting for plan approval
CONSUMER SERVICE, INFORMATION, AND
PAPERWORK (scale 1-4)
6 mo, customer serv, prob getting help
6 mo, prob understanding materials
6 mo, Paperwork probs
0.06 0.06
0.07 0.06
0.07 0.09
-0.05 -0.07
-0.03 -0.04
-0.07 -0.10
-0.06 -0.07
-0.06 -0.09
-0.06 -0.06
-0.04 -0.03
-0.09 -0.07
-0.04 -0.03
0.02
0.03
0.04
0.01
0.03
0.04
0.05
0.01
-0.03
-0.06
-0.02
-0.03
-0.03
-0.05
-0.03
-0.03
-0.09
-0.10
-0.08
-0.11
-0.09
-0.10
-0.10
-0.09
-0.08
-0.07
-0.06
-0.02
-0.07
-0.07
-0.06
-0.03
0.03
-0.01
0.03
0.01
0.03
-0.01
0.03
0.01
-0.06
-0.03
-0.04
-0.06
-0.05
-0.02
-0.04
-0.05
-0.09
-0.10
-0.09
-0.11
-0.11
-0.12
-0.11
-0.12
-0.09
-0.11
-0.10
-0.10
-0.09
-0.10
-0.10
-0.09
GETTING CARE QUICKLY (scale 1-5)
6 mo; got help/advice needed
6 mo; for routine care, saw Dr wanted
6 mo; got care as soon as wanted
b
6 mo; how often waited less than 15 mins
DOCTOR COMMUNICATION (scale 1-5)
6 mo, Dr. listened carefully
6 mo, Dr. explained well
6 mo, Dr. showed respect to you
6 mo, Dr. spent enough time with you
if |MA beta| > |ffs beta|
if |ffs beta| > |MA beta|
b
the scale for this variable has not been reversed since the question was changed: 1=Never - 4=Always (5=no visit)
182
Table E1d: Comparison of Magnitude of CMA Coefficients for the global ratings, FFS vs. MA
(2003)
STANDARDIZED COEFFICIENTS
AGE
EDUCATION
GHP
MHP
(7 levels)
(6 levels)
(5 levels)
(5 levels)
FFS MA
FFS MA
FFS MA
FFS MA
GLOBAL (scale 0=worst – 10=best)
How would you rate your personal doctor now
How would you rate your specialist now
Rate overall healthcare, past 6 months
Rate all experience with Medicare/health plan
0.03
0.02
0.04
0.15
0.04
0.02
0.04
0.08 *
-0.05
-0.04
-0.06
-0.07
-0.06
-0.06
-0.07
-0.06
-0.01
-0.04
-0.09
-0.05
-0.06 *
-0.07 *
-0.13 *
-0.13 *
-0.11
-0.12
-0.14
-0.08
-0.09
-0.11
-0.12
-0.07
0.02
0.03
0.03
0.08
0.03
0.03
0.02
0.05
-0.04
-0.02
-0.01
-0.03
-0.06 * -0.06 -0.12 * -0.06 -0.04
-0.02
-0.07 -0.09
-0.07 -0.05
-0.02
-0.07 -0.09
-0.07 -0.07
-0.05
-0.06 -0.10
-0.07 -0.04
GETTING NEEDED CARE (scale 1-4)
Was it a problem getting your choice of doctor
6 mo: Problem getting referral to specialist
6 mo: Problem getting care needed
6 mo: Problem waiting for plan approval
CONSUMER SERVICE, INFORMATION, AND PAPERWORK (scale 1-4)
6 mo: Problem getting help from customer service 0.05 0.04
6 mo: Problem understanding materials
0.03 0.04
6 mo: Paperwork problems
0.04 0.04
-0.04 -0.06
-0.01 -0.04
-0.06 -0.06
-0.08 -0.06
-0.07 -0.09
-0.05 -0.06
-0.00 -0.03
-0.08 -0.06
-0.06 -0.08
-0.09
-0.09
-0.09
-0.06
GETTING CARE QUICKLY (scale 1-5)
6 mo: Got help/advice needed
6 mo: Saw doctor wanted for routine care
6 mo: Got care as soon as wanted
6 mo: Taken to room within 15 minutes
0.02
0.03
0.03
-0.01
0.01
0.02
0.03
-0.01
-0.04
-0.05
-0.01
-0.01
-0.03
-0.04
-0.03
-0.00
-0.07
-0.07
-0.06
-0.08
-0.09
-0.09
-0.09
-0.08
-0.08
-0.08
-0.07
-0.05
0.02
-0.01
0.02
0.01
0.02
-0.01
0.02
0.01
-0.06
-0.03
-0.04
-0.06
-0.05
-0.02
-0.04
-0.05
-0.08
-0.09
-0.08
-0.10
-0.10
-0.10 -0.09
-0.11
-0.11 -0.10
-0.10 * -0.11 -0.10
-0.12
-0.11 -0.09
DOCTOR COMMUNICATION (scale 1-5)
6 mo: Doctor listened carefully
6 mo: Doctor explained well
6 mo: Doctor showed respect to you
6 mo: Doctor spent enough time with you
if |MA beta| > |ffs beta|
if |ffs beta| > |MA beta|
183
Table E2a: Explanatory Power of Group 1 (Base Model) Case-Mix Adjusters, Geo Unit
Reporting Entities, Years 2000 – 2001
Case-Mix Adjusters
Year:
Change in
R-square
20001,3
20012
Var(Geo Unit)
/Var(Error)
20001,3
20012
20001,3
20012
0.0156
0.0222
0.0575
0.0165
0.0049
0.0138
0.0251
0.0592
0.0094
0.0038
0.4354
0.1435
0.5624
0.0629
0.0043
0.3650
0.2457
0.5728
0.0385
0.0018
0.0156
0.0222
0.0575
0.0165
0.0049
0.0138
0.0251
0.0592
0.0094
0.0038
0.0644
0.4123
0.2626
0.0331
0.0057
0.0231
0.6190
0.4142
0.0112
0.0017
0.0156
0.0222
0.0575
0.0165
0.0049
0.0138
0.0251
0.0592
0.0094
0.0038
0.0203
0.1484
0.1438
0.0164
0.0066
0.0074
0.3434
0.1861
0.0024
0.0014
E.P.*1000
Medicare
AGE
GHP
EDUC
PROXY
ANSPROXY
0.0279
0.0065
0.0098
0.0038
0.0009
0.0265
0.0098
0.0097
0.0041
0.0005
Health Care
AGE
GHP
EDUC
PROXY
ANSPROXY
0.0041
0.0185
0.0046
0.0020
0.0012
AGE
GHP
EDUC
PROXY
ANSPROXY
0.0013
0.0067
0.0025
0.0010
0.0013
0.0017
0.0247
0.0070
0.0012
0.0005
Specialist
0.0005
0.0137
0.0031
0.0003
0.0004
Personal Doctor
0.0020
0.0156
0.0313
0.0006
0.0138
0.0085
0.0047
0.0222
0.1035
0.0062
0.0251
0.1550
0.0029
0.0575
0.1679
0.0050
0.0592
0.2957
0.0007
0.0165
0.0115
0.0005
0.0094
0.0046
0.0014
0.0049
0.0069
0.0008
0.0038
0.0030
1
Sample of 43 states common to MA and MFFS; excluding dually eligible beneficiaries.
2
Sample of 44 states common to MA and MFFS; excluding dually eligible beneficiaries.
3
The corresponding Table 8 in the Year 1 MFFS CMA Report used the sample of 50 states excluding the Dual
Eligible cases, and hence does not correspond exactly to Table 8a of the present report.
AGE
GHP
EDUC
PROXY
ANSPROXY
184
Table E2b: Explanatory Power of Group 2 (Prospective) Case-Mix Adjusters, Geo Unit
Reporting Entities, Excluding Dually Eligible Beneficiaries, Years 2000 – 2001
Case-Mix Adjusters
Year:
Change in
R-square
20001,3
20012
Var(Geo Unit)
/Var(Error)
20001,3
20012
20001,3
20012
0.0156
0.0160
0.0121
NA
NA
0.0182
NA
NA
0.0069
0.0145
0.0848
0.0190
0.1130
NA
NA
0.0908
NA
NA
0.0326
0.0285
0.0156
0.0160
0.0121
NA
NA
0.0182
NA
NA
0.0069
0.0145
0.2389
0.0272
0.2600
NA
NA
0.2116
NA
NA
0.0101
0.0015
0.0156
0.0160
0.0121
NA
NA
0.0182
NA
NA
0.0069
0.0145
0.1593
0.0182
0.1431
NA
NA
0.2100
NA
NA
0.0034
0.0001
E.P.*1000
Medicare
MHP
RPCS12
RMCS12
UNDER AGE 65
AGE 64 * GHP
0.0054
0.0012
0.0094
NA
NA
0.0050
NA
NA
0.0047
0.0020
Health Care
MHP
RPCS12
RMCS12
UNDER AGE 65
AGE 64 * GHP
0.0153
0.0017
0.0216
NA
NA
MHP
RPCS12
RMCS12
UNDER AGE 65
AGE 64 * GHP
0.0102
0.0011
0.0119
NA
NA
0.0116
NA
NA
0.0015
0.0001
Specialist
0.0115
NA
NA
0.0005
0.0000
Personal Doctor
0.0065
0.0156
0.1009
0.0058
0.0182
0.1065
0.0003
NA
0.0160
NA
0.0054
NA
0.0069
NA
0.0121
NA
0.0828
NA
NA
NA
NA
0.0001
0.0069
0.0007
NA
NA
NA
0.0012
0.0145
0.0177
1
Sample of 43 states common to MA and MFFS.
2
Sample of 44 states common to MA and MFFS.
3
The corresponding Table 8 in the Year 1 MFFS CMA Report used the sample of 50 states excluding the Dual
Eligible cases, and hence does not correspond exactly to Table 8a of the present report.
MHP
RPCS12
RMCS12
UNDER AGE 65
AGE 64 * GHP
Note: ‘UNDER AGE 65’ is a linear coding of the following three age categories: 18 to 39, 4054, and 55-64. ‘AGE 64 * GHP’ is the interaction of an indicator of age under 65 with a linear
coding of GHP.
185
Table E3: Comparison of 2000- 2002 MFFS CMA Coefficients for the 2000-2001 Base Model (no MHP), 43/44 States Common
with MA, Excluding Dually Eligible Beneficiaries, Geo Unit Dummies
Rate Doctor
Rate Specialist
Rate Medicare
Rate health Care
Years:
AGE
AGE44
AGE64
AGE4564
AGE6569
AGE80
AGE7579
AGE8084
AGE85
EDUCATION
LESS8GRD
SOMEHIGH
SOMECOLL
COLLGRAD
COLLMORE
GHP
EXCEL
VERYGOOD
FAIR
POOR
PROXY
PROXY
ANSPROXY
20001
20012
20023
20001
20012
0.03
-0.01
0.09
*
-0.11
-0.07
0.07
0.07
0.09
0.09
0.09
0.15
0.12
0.15
0.08
20012
-0.15
*
20023
20001
20012
-0.64
-0.13
-0.27
-0.20
-0.02
0.11
0.07
20001
-0.35
0.19
-0.14
20023
20023
-1.48
*
-0.90
-0.80
-0.10
*
-0.76
-0.06
-0.12
-0.05
-0.12
-0.09
-0.07
-0.30
-0.27
-0.31
0.06
0.01
0.06
0.06
0.05
0.08
0.18
0.21
0.24
-0.01
-0.04
0.08
0.02
0.04
0.04
0.10
0.11
0.34
0.38
0.39
0.43
0.06
0.05
0.07
0.05
0.03
0.04
0.06
0.08
0.31
*
0.05
0.10
0.13
0.12
0.07
0.12
0.12
*
-0.10
-0.12
-0.08
-0.14
-0.18
-0.13
-0.25
-0.27
-0.24
-0.33
0.50
0.10
0.14
0.13
-0.06
-0.12
-0.08
-0.21
-0.20
-0.22
-0.23
-0.17
-0.22
-0.17
-0.19
-0.17
-0.23
-0.17
-0.19
0.39
0.45
0.43
0.28
0.46
0.43
0.17
0.19
0.18
0.15
0.22
0.19
-0.08
-0.11
-0.09
-0.10
-0.16
-0.23
*
*
-0.13
-0.26
-0.19
-0.36
-0.24
-0.42
-0.16
-0.14
-0.09
*
-0.16
-0.07
-0.08
-0.26
-0.26
-0.21
-0.30
-0.18
-0.10
1
Sample of 43 States
2
Sample of 44 States
3
Sample of 43 States
* p-val <0.05
186
0.04
*
*
*
*
*
*
0.05
0.14
0.11
0.11
-0.25
-0.27
-0.24
-0.21
-0.30
-0.40
-0.53
-0.41
-0.53
-0.35
-0.50
0.55
0.55
0.36
0.36
0.40
0.23
0.28
0.25
*
0.15
0.19
0.19
-0.17
-0.34
-0.20
-0.38
-0.27
-0.51
*
*
-0.07
-0.19
-0.10
-0.28
-0.21
-0.53
-0.20
-0.16
-0.13
*
-0.33
-0.33
-0.30
-0.25
-0.19
-0.15
-0.20
-0.23
-0.13
*
*
*
APPENDIX F: ISSUES REGARDING CASE-MIX ADJUSTMENT FOR MODE (2002
DATA)
Phone mode of administration has a compelling large empirical estimated effect. Its
explanatory power may be equal to that of any case-mix adjustor currently employed. In
addition, the tendency for more positive responses on the phone is consistent with the wellestablished finding that socially desirable response bias (such as rating health care or Medicare
positively) is stronger in survey modes that involve more social interaction (face-to-face,
telephone) than in more anonymous modes (computer assisted, written). Vince Ianaccione at
RTI led the investigation of this pattern in the MFFS survey.
Rates of telephone completion are notably higher in MA (17.2%) than in MFFS (15.3%);
in eight states the phone rate is higher in MA than in MFFS by 4% or more, including
Mississippi (29.4% phone in MA, 17.9% in MFFS). Only Hawaii (8.8% phone for MA, 13.0%
phone for MFFS) shows a strong reversal of this trend. This pattern suggests the possibility that
MA has benefited from socially desirable response bias in a systematic manner to a greater
extent than MFFS, and that the comparisons might be more equitable with an adjustment for
mode. Because the state-level variance in phone-completion rates is 2.1 times as high in MA
than in MFFS, the potential for high explanatory power for phone mode is perhaps even greater
in MFFS-vs.-MA CMA than the large effects already observed in within-MFFS CMA.
Unfortunately, there are several theoretical and empirical difficulties in implementing
mode as a case-mix adjustor. First, the current approach assumes that the mode effects observed
among MFFS late-responders hold equally for early responders. This assumption should
probably be empirically verified through a mode experiment in MFFS that involves random
assignment of some beneficiaries from the start of the process. Second, for pure mode effects to
be estimated within MA, a mode experiment involving random assignment would have to take
place within the MA survey. Furthermore, because this adjustment involves estimation of
coefficients effects within randomly assigned subpopulations followed by projection of these
coefficients to the larger population of all phone respondents (self-selected as well), this could
not be implemented in the current CAHPS Macro without further modification. Likewise, the use
of this approach in subgroup and other regressions could not be accomplished by the simple use
of dummy variables in a single step. Finally, unless the mode experiments were sufficiently
large, the mode coefficients could be subject to larger standard errors than other CMA
coefficients.
187
REFERENCES
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